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Position: Generative Engine Optimization Creates Underexamined Risks, Governance Must Target Concentration, Disclosure, and Academic Blind Spots
AVI-Bench: Toward Human-like Audio-Visual Intelligence of Omni-MLLMs
RoCA: Robust Cross-Domain End-to-End Autonomous Driving
Position: Token Taxes Can Mitigate AI's Economic Risks
Hyper-ICL: Attention Calibration with Hyperbolic Anchor Distillation for Multimodal In-Context Learning
Temporal Context Reinstatement Drives Episodic-Like Order Memory in Long-Context Language Models
Beyond Procedure: Substantive Fairness in Conformal Prediction
FOCA: Future-Oriented Conditioning for Data-Efficient Vision-Language-Action Adaptation
Optimal Fair Aggregation of Crowdsourced Noisy Labels using Demographic Parity Constraints
AdaGC: Enhancing LLM Pretraining Stability via Adaptive Gradient Clipping
Proteus: Lookup-Free Trellis-Coded Quantization by Lattice-Breaking Compute Codes for 2-Bit LLMs
Continuity-Regularized Flow Matching for Offline Reinforcement Learning
Reward-Preserving Counterfactual State Editing for Offline Reinforcement Learning
3D Scene Assertion Verification
Steal the Patch Size: Adversarially Manipulate Vision Language Models
SARSteer: Safeguarding Large Audio Language Models via Safe-Ablated Refusal Steering
Position: Safe Models Do Not Guarantee Safe Societies: The Case for Sociopolitical Risk
Hybrid Policy Distillation for LLMs
ML-Embed: Inclusive and Efficient Embeddings for a Multilingual World
ScaLoRA: Optimally Scaled Low-Rank Adaptation for Efficient High-Rank Fine-Tuning
Test-Time Anchoring for Discrete Diffusion Posterior Sampling
Fast kernel methods: Sobolev, physics-informed, and additive models
Scalable and Differentiable Point-Cloud Registration Using Maximum Mean Discrepancy
From Talking to Singing: A New Challenge for Audio-Visual Deepfake Detection
What Language is This? Ask Your Tokenizer.
Domain Adaptive Object Detection via Dynamic Causal Refinement
Overcoming the Incentive Collapse Paradox
TFRBench: A Reasoning Benchmark for Evaluating Forecasting Systems
NOMAD: Lifelong Trajectory Planning via Non-Parametric Bayesian Memory-Adaptive Diffusion Experts
To Grok Grokking: Provable Grokking in Ridge Regression
Incremental BPE Tokenization
Revisiting Neural Processes via Fourier Transform and Volterra Series
Position: Stop Automating Peer Review Without Rigorous Evaluation
Cross-View Lewis Weight Fusion Empowering Exemplar Replay for Federated Class-Incremental Learning
Federated Data and Feature Selection by Generalized CUR Decomposition
Feature Bagging Provides Stability
Generative Adaptation of Dynamics to Environmental Shifts via Weight-space Diffusion
Beyond Accuracy and Complexity: The Effective Information Criterion for Structurally Stable Symbolic Regression
SynerMedGen: Synergizing Medical Multimodal Understanding with Generation via Task Alignment
Position: The Privacy-Auditability Paradox in Federated Learning: Why We Need Controllable Secure Aggregation
CausalArmor: Efficient Indirect Prompt Injection Guardrails via Causal Attribution
Beyond Normalization: Rethinking the Partition Function as a Difficulty Scheduler for RLVR
A Penalty Approach For Differentiation Through Black-box Quadratic Programming Solvers
DIVA: Harnessing the Representation Divergence in Unified Multimodal Models for Mutual Reinforcement
RGMem: Renormalization Group–inspired Memory Evolution for Language Agents
Privacy Amplification in Differentially Private Zeroth-Order Optimization with Hidden States
Resource-Efficient Reinforcement for Reasoning Large Language Models via Dynamic One-Shot Policy Refinement
Prototype-guided Bilateral Alignment Multimodal Federated Learning
MA$^3$S: Model-Agnostic Active Annotation Strategy for Crowdsourcing
Swift-SVD: Theoretical Optimality Meets Practical Efficiency in Low-Rank LLM Compression
Identifying Partially Observed Causal Models from Heterogeneous/Nonstationary Data
Learning General Causal Structures with Hidden Dynamic Process for Climate Analysis
ReSeek: A Self-Correcting Framework for Search Agents with Instructive Rewards
Position: Child Safety Necessitates New Approaches to AI Safety
Plasticity Activation via Polar Operator: A Plug-in Method for Balancing Stability and Plasticity
WorldCache: Accelerating World Models for Free via Heterogeneous Token Caching
Fast-SAM3D: 3Dfy Anything in Images but Faster
Full-Spectrum Graph Neural Networks: Expressive and Scalable
Implicit Preference Alignment for Human Image Animation
Mixture Prototype Flow Matching for Open-Set Supervised Anomaly Detection
Anomaly-Preference Image Generation
Position: Let’s Build a Trustworthy Model Context Protocol!
Position: It is Time to Virtualize Foundation Models with a Self-evolving Operating System Layer
RouteFinder: Towards Foundation Models for Vehicle Routing Problems
Position: When AI Decides Who Gets an Organ: Multi-Agentic AI Systems in Transplant Medicine Risk Amplifying Disparities Without Targeted Explainability and Deployment Strategies
Step-Level Sparse Autoencoder for Reasoning Process Interpretation
The Fisher Dimension: Instance-Dependent Complexity for Causal Discovery
Flash-VAED: Plug-and-Play VAE Decoders for Efficient Video Generation
TWLA: Achieving Ternary Weights and Low-Bit Activations for LLMs via Post-Training Quantization
Interpretable Embeddings with Sparse Autoencoders: A Data Analysis Toolkit
Group-wise Data Ordering: Enhancing Instruction Tuning of Large Language Models via Embedding Proximity
DiL: Discrete-anchored Representation Alignment for Semi-Supervised Continual Learning
Replay Failures as Successes: Sample-Efficient Reinforcement Learning for Instruction Following
Contrastive Reasoning Alignment: Reinforcement Learning from Hidden Representations
Pseudo-Mallows for Efficient Probabilistic Preference Learning
Geometry-Aware Neural Optimizer for Shape Optimization and Inversion
TIME: Tensor-Factorized Mixture-of-Experts with Intrinsic Routing for Lifelong Multimodal Knowledge Editing
World Guidance: World Modeling in Condition Space for Action Generation
Position: The Alignment Community is Unintentionally Building a Censor’s Toolkit
Decoding Safety Feedback from Diverse Raters: A Data-driven Lens on Responsiveness to Severity
ETS: Energy-Guided Test-Time Scaling for Training-Free RL Alignment
Position: Solipsistic superintelligence is unlikely to be cooperative
Fairness in Aggregation: Optimal Top-$k$ and Improved Full Ranking
BEAR: Dissecting Embodied Abilities in Multimodal Language Models through Skill-level Evaluation and Diagnosis
HelioX: A GPU-Native Framework for Simulation and Training of Biophysically Detailed Networks
Reinforcement Learning with Verifiable Rewards: GRPO's Loss, Dynamics, and Success Amplification
Simple Approximation and Derivative Free Inference-Time Scaling for Diffusion Models via Sequential Monte Carlo on Path Measures
TSMGen: Target-Specific Molecule Generation via Higher-Order Structural Dependencies and Context-Aware Bidirectional Fusion
Off-Policy Evaluation for Missingness-Aware Policies in MDPs with Rewards Missing Not at Random
ParamMem: Augmenting Language Agents with Parametric Reflective Memory
HieraMAS: Optimizing Intra-Node LLM Mixtures and Inter-Node Topology for Multi-Agent Systems
Linear-Core Surrogates: Smooth Loss Functions with Linear Rates for Classification and Structured Prediction
The Personality Illusion: Revealing Dissociation Between Self-Reports & Behavior in LLMs
RE-TRAC: REcursive TRAjectory Compression for Deep Search Agents
(De)-regularized Maximum Mean Discrepancy Gradient Flow
KernelBand: Steering LLM-based Kernel Optimization via Hardware-Aware Multi-Armed Bandits
Likelihood Matching for Diffusion Models
EVOLVING ROLLOUTS: Harnessing Historical Experience for Web Agent Evolution in Reinforcement Learning
Enhancing Neural Theorem Proving via High-Quality Proof Selection and Verifier Feedback
Offline Preference Optimization for Rectified Flow with Noise-Tracked Pairs
AAD-1: Asymmetric Adversarial Distillation for One-Step Autoregressive Video Generation
A Language-Guided Bayesian Optimization for Efficient LoRA Hyperparameter Search
Exploring Motif-based Heterogeneous Graph Learning for ReDoS Detection
Temporal Weighted Encoding: Towards Maximal-Capacity Spike Coding for ANN–SNN Conversion
Label-Guided Representation Learning for Incomplete Multi-View Multi-Label Classification
Position: The Case for Theory-Level Autoformalization
Position: Interpretability Can Be Actionable
When Sample Selection Bias Precipitates Model Collapse
AdamO: A Collapse-Suppressed Optimizer for Offline RL
The Realignment Problem: When Right becomes Wrong in LLMs
Toward Culturally Aligned LLMs through Ontology-Guided Multi-Agent Reasoning
RTPrune: Reading-Twice Inspired Token Pruning for Efficient DeepSeek-OCR Inference
DocHop: Benchmarking Out-of-domain Multi-hop Reasoning in Information-Dense Documents
CLINIC : Evaluating Multilingual Trustworthiness in Language Models for Healthcare
Position: Natural Language Should Not Fully Replace Formal Languages
Position: Express Your Doubts — Probabilistic World Modeling Should not be Based on Token *logprobs*
Causal Preference Elicitation
Reward Shaping for (Inference-Time) Alignment: A Stackelberg Game Perspective
On the Coordination of Value-Maximizing Bidders
From Knowledge to Inference: Formalizing Specialized Public Health Reasoning on GlobalHealthAtlas
UCPO: Uncertainty-Aware Policy Optimization
LightAVSeg: Lightweight Audio-Visual Segmentation
LLM4Branch: Large Language Model for Discovering Efficient Branching Policies of Integer Programs
NL2Repo-Bench: Towards Long-Horizon Repository Generation Evaluation of Coding Agents
SE3Set: Harnessing Equivariant Hypergraph Neural Networks for Molecular Representation Learning
Structured 4D Latent Predictive Model for Robot Planning
VLM-RobustBench: A Comprehensive Benchmark for Robustness of Vision-Language Models
Evaluating Parameter Efficient Methods for RLVR
Online Bayesian Experimental Design for Partially Observed Dynamical Systems
Complexity Bounds for Dirichlet Process Slice Samplers
Continual Learning of Domain-Invariant Representations
Rethinking GNNs and Missing Features: Challenges, Evaluation and a Robust Solution
Structured Expert Routing with Multi-View Task Priors for Offline Meta-Reinforcement Learning
Multi-timescale Reinforcement Learning by Value Reconstruction
Do Vision and Text Cues Exhibit Evidential Coupling? UFO: A Benchmark for Compositional Multimodal Reasoning in Unified Models
General Analysis of LMO-based Optimizers: Beyond Bounded Variance
Moving Out: Physically-grounded Human-AI Collaboration
Constrained Multi-Objective Reinforcement Learning with Max-Min Criterion
UnHype: CLIP-Guided Hypernetworks for Dynamic LoRA Unlearning
Mixing Configurations for Downstream Prediction
See What Matters: Differentiable Grid Sample Pruning for Generalizable Vision-Language-Action Model
SP-Mind: An Autonomous Reasoning Agent for Spatial Proteomics Analysis
Is Your LLM Overcharging You? Tokenization, Transparency, and Incentives
Global Directional Priors with Local Statistical Validation for Scalable Causal Discovery
Boosting Monocular Metric Depth Estimation via Bokeh Rendering
S2M-Net: Spectral-Spatial Mixing with Morphology-Aware Adaptive Loss for Medical Image Segmentation
The Latent Color Subspace: Emergent Order in High-Dimensional Chaos
ScenePilot: Controllable Boundary-Driven Critical Scenario Generation for Autonomous Driving
ZeroBench: An Impossible Visual Benchmark for Contemporary Large Multimodal Models
TimeSpot: Benchmarking Geo-Temporal Understanding in Vision–Language Models in Real-World Settings
Position: Irresponsible AI: big tech’s influence on AI research and associated impacts
Smoothness Errors in Dynamics Models and How to Avoid Them
Zono-Conformal Prediction: Zonotope-Based Uncertainty Quantification for Regression and Classification Tasks
CATArena: Evaluating Evolutionary Capabilities of Code Agents via Iterative Tournaments
WISE: World Knowledge-Informed Semantic Evaluation for Text-to-Image Generation
Position: Code Benchmarks Should Prioritize Rigor, Reliability, and Reproducibility
Persona2Web: Benchmarking Personalized Web Agents for Contextual Reasoning with User History
Segmentation From Attention: Training-Free Layer Selection and One-Shot Tuning for Segmentation in VLMs
Position: AI/ML Deepfake Research is Misaligned with AI Generated Non-Consensual Intimate Imagery (AIG-NCII)
Position: Assistive Agents Need Accessibility Alignment
Position: The Age of AI Agents Demands A New Scientific Paradigm To Sustain Trustworthy Science
Retrospective Feature Estimation for Continual Learning
Position: Agent Security Needs Redefinition through a Holistic Framework
Position: Evidence and Implications of Texture Bias in Deep Neural Networks
Position: Current Benchmarking Hinders Real Progress in Deep Learning for Time Series Forecasting
Position: `AI Alignment' Encompasses Competing Technical Priorities
Population-Free Pareto Tracking for Sample-Efficient Multi-Policy MORL
Position: We Need A Unified Definition of Hallucination (It’s The World Model, Stupid!)
Meta-Learning with Generalized Ridge Regression: High-dimensional Asymptotics, Optimality and Hyper-covariance Estimation
Position: Model identity in machine learning is a convention, not a property
Reasoning-Driven Synthetic Data Generation and Evaluation
Position: In Defense of Information Leakage in Concept-based Models
Random Erasing vs. Model Inversion: A Promising Defense or a False Hope?
Position: Universal Aesthetic Alignment Narrows Artistic Expression
FedLog: Personalized Federated Classification with Less Communication and More Flexibility
PruneFuse: Efficient Data Selection via Weight Pruning and Network Fusion
Position: Profiling Game Worlds by Transition Complexity
Position: Privacy Is a Claim, Not a Property of Synthetic Data
Position: Current Model Cards Are Insufficient for Downstream Governance of Open-Weight Foundation Models
Position: Carbon Footprint Reporting Should Be Routine in Machine Learning Research
Position: Bridge the Gaps between AI Development and Regulation
Position: Medical AI Neglects Real Treatment Outcomes
Position: The Time for Sampling Is Now! Charting a New Course for Bayesian Deep Learning
Position: If open source is to win, it must go public
What Makes a Strong Model? A Unified Spectral Analysis of Knowledge Transfer over High-dimensional Linear Regression
Optimization Dynamics of Equivariant and Augmented Neural Networks
Position: The Data Provenance–Parametric Divide in Large Language Models
Position: Explanation Stability Is a Property of the Model–Method Pair, Not the Model
Position: Self-Play Only Evolves When Self-Synthetic Pipeline Ensures Learnable Information Gain
Position: Uncertainty is a Strategic Signal in Human–AI Decision Making
Reinforcement Learning from Bagged Reward
Tracing the Persona Circuit: How Large Language Models Encode and Express Character Traits
Understanding Dynamics of Adam in Zero-Sum Games: An ODE Approach
CARE: Adaptive Calibration for Reliable Recommendations
UDM-GRPO: Stable and Efficient Group Relative Policy Optimization for Uniform Discrete Diffusion Models
Discovering Scaling Exponents with Physics-Informed Müntz-Szász Networks
Return-Aligned Decision Transformer
The Choice of Normalization Influences Shrinkage in Regularized Regression
Learning Coherent Representations: A Topological Approach to Interpretability
How Hard Is Science?
DuFal: Dual-Frequency-Aware Learning for High-Fidelity Extremely Sparse-view CBCT Reconstruction
Position: Topological Machine Learning Cannot Progress without Experimental Standards
DynaTok: Token-Based 4D Reconstruction from Partial Point Clouds
Anchored Decoding: Provably Reducing Copyright Risk for Any Language Model
Towards Understanding Massive Activations in Attention Sink Mechanism
Position: LLM-Safety Evaluations Lack Robustness
Position: Stop Using Culturally Biased Human Cognitive Benchmarks to Evaluate LLMs
Position: Towards Responsible Evaluation for Text-to-Speech
Online Tensor Learning: Computational and Statistical Trade-offs, Adaptivity and Optimal Regret
UniFast-HGR: Scalable and Efficient Maximal Correlation for Multimodal Models
LiveOIBench: Can Large Language Models Outperform Human Contestants in Informatics Olympiads?
LumiNet: Perception-Driven Knowledge Distillation via Statistical Logit Calibration
Position: Behavioral Systems Require Behavioral Tests
Position: No Retroactive Cure for Infringement during Training
RaBiT: Residual Aware Binarization Training for Accurate and Efficient LLMs
Riemannian Generative Decoder
Optimal Transport under Group Fairness Constraints
Self-Refining Video Sampling
MixtureVitae: Open Web-Scale Pretraining Dataset With High Quality Instruction and Reasoning Data Built from Permissive-First Text Sources
Selective Concept Bottleneck Models Without Predefined Concepts
Position: Verifiable Data Minimization is a Prerequisite for Responsible, Privacy-Preserving Industrial Vision
FlexRank: Nested Low-Rank Knowledge Decomposition for Adaptive Model Deployment
MoFO: Momentum-Filtered Optimizer for Mitigating Forgetting in LLM Fine-Tuning
Learning to Perceive the World Through Control: Empowerment-Based Representation Learning
DASH: Faster Shampoo via Batched Block Preconditioning and Efficient Inverse-Root Solvers
Nash Equilibria in Games with Playerwise Concave Coupling Constraints: Existence and Computation
Transport Clustering: Solving Low-Rank Optimal Transport via Clustering
HybridOM: Hybrid Physics-Based and Data-Driven Global Ocean Modeling with Efficient Regional Downscaling
Accordion-Thinking: Self-Regulated Step Summaries for Efficient and Readable LLM Reasoning
Maximum Likelihood Reinforcement Learning
DP-KFC: Data-Free Preconditioning for Privacy-Preserving Deep Learning
Through the Stealth Lens: Attention-Aware Defenses Against Poisoning in RAG
Depth-Breadth Synergy in RLVR: Unlocking LLM Reasoning Gains with Adaptive Exploration
Deep Flow Networks
Orthogonal Concept Erasure for Diffusion Models
Learning Rewrite-Invariant Reasoning with Targeted Alternation Training
Less Is More: Elevating RAG via Performance-Driven Context Compression
Position: Neural Approximation Is Rarely Justified for Hard Combinatorial Problems
FormalRx: Rectify and eXamine Semantic Failures in Autoformalization
Optimizing Diversity and Quality through Base-Aligned Model Collaboration
Beyond the Bellman Recursion: A Pontryagin-Guided Framework for Non-Exponential Discounting
Chain-of-Glimpse: Search-Guided Progressive Object-Grounded Reasoning for Video Understanding
ANCHOR: Automated Alignment Auditing for CLI Agents on Real-World Harm
CauSciBench: Can LLMs Automate Causal Inference in Real-World Scientific Research?
Dream-MPC: Gradient-Based Model Predictive Control with Latent Imagination
Smaller Models are Natural Explorers for Policy-Level Diversity in GRPO
Behavioral Mode Discovery for Fine-tuning Multimodal Generative Policies
STAR-KV: Low-Rank KV Cache Compression via Soft Thresholding for Adaptive Rank Control
ProAct: A Benchmark and Multimodal Framework for Structure-Aware Proactive Response
Training–Inference Consistent Segmented Execution for Long-Context LLMs
Lottery Prior: Randomized Neural Compression for Zero-Shot Inverse Problems
Discrete Diffusion VLA: Bringing Discrete Diffusion to Action Decoding in Vision-Language-Action Policies
Chiral Symmetry Breaking in Transformers: A Group-Equivariant Framework for Addressing the Reversal Curse via Adjoint Manifold Mappings
Position: Modular Memory is the Key to Continual Learning Agents
TreeCUA: Efficiently Scaling GUI Automation with Tree-Structured Verifiable Evolution
High-accuracy and dimension-free sampling with diffusions
DDIM Inversion as a Perturbation Amplifier: Breaking Mimicry Protection via Reconstruction Error Minimization
TruthRL: Incentivizing Truthful LLMs via Reinforcement Learning
Geometry-Aware Contrastive Learning for Few-Shot Automatic Modulation Recognition
Learning in Structured Stackelberg Games
Fully Dynamic Coreset Spectral Clustering
Position: Digital Agents Require Unified Agent-Native Environments
AutoControl Arena: Synthesizing Executable Test Environments for Frontier AI Risk Evaluation
GSFixer: Improving 3D Gaussian Splatting with Reference-Guided Video Diffusion Priors
T-Edit: Triple-Branch Diffusion Anchoring for Consistent Editing
HTAC: Hierarchical Task-Aware Composition for Continual Offline Reinforcement Learning
CoMem: Context Management with A Decoupled Long-Context Model
UltraHorizon: Benchmarking LLM-Agent Capabilities in Ultra Long-Horizon Scenarios
U-Cast: A Surprisingly Simple and Efficient Frontier Probabilistic AI Weather Forecaster
Semi-knockoffs: a model-agnostic conditional independence testing method with finite-sample guarantees
Unlearning’s Blind Spots: Over‑Unlearning and Prototypical Relearning Attack
AugServe: Adaptive Request Scheduling for Augmented Large Language Model Inference Serving
Length Generalization Bounds for Transformers
Cross-Chirality Generalization by Axial Vectors for Hetero-Chiral Protein-Peptide Interaction Design
ManiSoft: Towards Vision-Language Manipulation for Soft Continuum Robotics
SS-TPT: Stability and Suitability-Guided Test-Time Prompt Tuning for Adversarially Robust Vision-Language Models
Efficient Parallel Samplers for Recurrent-Depth Models
VIPO: Value Function Inconsistency Penalized Offline Reinforcement Learning
GEPC: Group-Equivariant Posterior Consistency for Out-of-Distribution Detection in Diffusion Models
Position: It’s Time to Optimize for Self-Consistency
SAC-Opt: Semantic Anchors for Iterative Correction in Optimization Modeling
Early Directional Convergence in Deep Homogeneous Neural Networks for Small Initializations
Test-Time Reinforcement Learning for Flow Matching
Concept Removal for Frontier Image Generative Models
Differentially Private Submodular Maximization with a Knapsack Constraint
From Static Constraints to Dynamic Adaptation: Sample-Level Constraint Relaxation for Offline-to-Online Reinforcement Learning
What Does Preference Learning Recover from Pairwise Comparison Data?
Position: LLM for Physics Research Requires Domain-Specialized Training and Tooling
One-step Latent-free Image Generation with Pixel Mean Flows
Autobidding Auctions with LLM-Powered Creatives
LO-BCQ: Locally Optimal Block Clustered Quantization for 4-bit (W4A4) LLM Inference
EffGen: Enabling Small Language Models as Capable Autonomous Agents
One Tool Is Enough: Reinforcement Learning of LLM Agents for Repository-Level Code Navigation
Spik4lite: Refactoring Neuromorphic Sparsity for Efficient Spiking Neural Networks on Commodity Edge Devices
Position: Don't Just "Fix it in Post'': A Science of AI Must Study Learning Dynamics
Skip-It? Theoretical Conditions for Layer Skipping in Vision–Language Models
NExT-Guard: Training-Free Streaming Safeguard without Token-Level Labels
Rate or Fate? RLV$^{\varepsilon}$R: Reinforcement Learning with Verifiable Noisy Rewards
SafeSci: Safety Evaluation of Large Language Models in Science Domains and Beyond
Contrastive Weak-to-Strong Generalization
Memory as a Markov Matrix: Sample Efficient Knowledge Expansion via Token-to-Dictionary Mapping
The Shape of Addition: Geometric Structures of Arithmetic in Large Language Models
MMBench-Live: A Continuously Evolving Benchmark for Multimodal Models
NaRA: Noise-Aware LoRA for Parameter-Efficient Fine-Tuning of Diffusion LLMs
MindZero: Learning Online Mental Reasoning With Zero Annotations
Revisiting Robustness for LLM Safety Alignment via Selective Geometry Control
When Can You Poison Rewards? A Tight Characterization of Reward Poisoning in Linear MDPs
Operationalising the Superficial Alignment Hypothesis via Task Complexity
R-Diverse: Mitigating Diversity Illusion in Self-Play LLM Training
Spectral Evolution Search: Efficient Inference-Time Scaling for Reward-Aligned Image Generation
FlashSinkhorn: IO-Aware Entropic Optimal Transport on GPU
Principle-Evolvable Scientific Discovery via Uncertainty Minimization
Neural Concept Verifier: Scaling Prover-Verifier Games via Concept Encodings
Designing a Conditional Prior Distribution for Flow-Based Generative Models
ConEx: Human-Interpretable Saliency Maps via Concept-Aware Attribution
BioToken and BioFM – Biologically-Informed Tokenization Enables Accurate and Efficient Genomic Foundation Models
SpecPrune-VLA: Accelerating Vision-Language-Action Models via Action-Aware Self-Speculative Pruning
Revisiting ML Training under Fully Homomorphic Encryption: Convergence Guarantees, Differential Privacy, and Efficient Algorithms
Emergent Alignment via Competition
Making Learner Weakness Actionable for Learning from Demonstration with Novice Teachers
Video2GUI: Synthesizing Large-Scale Interaction Trajectories for Generalized GUI Agent Pretraining
Position: Knowing Isn’t Understanding: Re-grounding Generative Proactivity with Epistemic and Behavioral Insight
Deep Reinforcement Learning Finds Bayes-Nash Equilibrium in Competitive Newsvendor Problems
C$^{2}$R: Cross-sample Consistency Regularization Mitigates Feature Splitting and Absorption in Sparse Autoencoders
Fourier Features Let Agents Learn High Precision Policies with Imitation Learning
Fractional is Better: Learnable Derivative Orders in Neural Operator Learning
PS-PPO : Prefix-Sampling PPO for Critic-Free RLHF
Optimal Transport Group Counterfactual Explanations
Beyond Prediction: Tail-Aware Scheduling for LLM Inference
Inference Time Concept Removal Guidance for Text-to-Image Diffusion Models
Twins: Learn to Predict Unified Representations with Focal Loss
CLoVE: Personalized Federated Learning through Clustering of Loss Vector Embeddings
Both Semantics and Reconstruction Matter: Making Representation Encoders Ready for Text-to-Image Generation and Editing
MapUQ: Map with Uncertainty Quantification for Robust BEV Vectorized Construction
CACR: Reinforcing Temporal Answer Grounding in Instructional Video via Candidate-Aware Causal Reasoning
Position: Genomic Model Research Must Move Beyond Anecdotal Evaluation of Interpretability Methods
Grounding Functional Similarity by Invariance-Aware Model Stitching
OBJVanish: Prompt-Driven Generation of Physically Realizable 3D LiDAR-Invisible Objects
Pruning at Initialisation through the lens of Graphon Limit: Convergence, Expressivity, and Generalisation
Manifold-Aware Perturbations for Constrained Generative Modeling
Principled Zero-shot Ranking Agents with Tournament Graphs
LoPhyDA: Low-Rank Tensor and Physics Gradient Guided Diffusion for Atmospheric Data Assimilation
Test-time Generalization for Physics through Neural Operator Splitting
Discretized Density-Guided Source-Free Adaptation for Continuous Targets
Efficient Learned Image Compression without Entropy Coding
Unpaired Visual Editing with Self-Consistent Flow Matching
Online Learning and Inference for Cox Proportional Hazards Model Using Renewable Sieve Estimation
Walrus: A Cross-domain Foundation Model for Continuum Dynamics
One Batch Is Enough: A Unified Dataset Condensation Framework for General Time Series Analysis
(Sparse) Attention to the Details: Preserving Spectral Fidelity in ML-based Weather Forecasting Models
Equivariant Neural Networks for General Linear Symmetries on Lie Algebras
Feature Resemblance: Towards a Theoretical Understanding of Analogical Reasoning in Transformers
Benchmarking LLM-Assisted Blue Teaming via Standardized Threat Hunting
Position: Time to Close The Validation Gap in LLM Social Simulations
Mirror Descent Policy Optimisation for Robust Constrained Markov Decision Processes
SALAAD: Sparse And Low-Rank Adaptation via ADMM for Large Language Model Inference
BrainJanus: A Unified Model for Understanding and Generation across Brain, Vision, and Language
[CLS] is Not Enough: Multi-Label Recognition via Patch-Level Inference and Adaptive Aggregation
Finite-Width Neural Tangent Kernels from Feynman Diagrams
A unified theory of feature learning in RNNs and DNNs
Geometry-Preserving Unsupervised Alignment for Heterogeneous Foundation Models
Let EEG Models Learn EEG
Beyond Structural Symmetries: Linear Mode Connectivity via Neuron Identifiability
Embedding-perturbed Exploration Preference Optimization for Flow Models
Enhancing Train-Free Infinite-Frame Generation for Consistent Long Videos
Matrix-Free GPU Semidefinite Programming for Quantum Ordered Search at the k=6 Frontier
Position: Vector Prompt Interfaces Should Be Exposed to Enable Customization of Large Language Models
Scalable Bayesian Inference for Nonlinear Conservation Laws
The Implicit Bias of Depth: From Neural Collapse to Softmax Codes
Diffusion posterior sampling for simulation-based inference in tall data settings
Gradient Regularization Mitigates Reward Hacking in Reinforcement Learning from Human Feedback and Verifiable Rewards
Learning Permutation-invariant Macroscopic Dynamics
Do-Prompt: Causal Interventions Meet Variational Prompt Bottlenecks
Residual-Guided Multi-Resolution Refinement of Foundation Models: A Case Study in Drought Forecasting
Efficient DP-SGD for LLMs with Randomized Clipping
Memory Caching: RNNs with Growing Memory
REAL: Regression-Aware Reinforcement Learning for LLM-as-a-Judge
LABO: LLM-Accelerated Bayesian Optimization through Broad Exploration and Selective Experimentation
Diffusion Differentiable Resampling
Provably Protecting Fine-Tuned LLMs from Training Data Extraction while Preserving Utility
Expressivity-Efficiency Tradeoffs for Hybrid Sequence Models
StableI2I: Spotting Unintended Changes in Image-to-Image Transition
Stop When Further Reasoning Won’t Help: Attention-State Adaptive Generation in Reasoning Models
Breaking the Block: Preserving Data Continuity to Train Superior SAEs for Instruct Models
ClimateAR: Multi-Scale Autoregressive Generative Modeling for Climate Forecasting
PADA-Coder: Improving Plan-Following Code Generation via Perturbation-Verified Attention Distillation and Dynamic Alignment
Position: LLM-Based Social Simulations Require a Boundary
Nonparametric LLM Evaluation from Preference Data
UniPercept: Towards Unified Perceptual-Level Image Understanding across Aesthetics, Quality, Structure, and Texture
A Geometric Lens on Physics-Aligned Data Compression
TsLLM: Augmenting LLMs for General Time Series Understanding and Prediction
Recurrent Equivariant Constraint Modulation: Learning Per-Layer Symmetry Relaxation from Data
CoME: Empowering Channel-of-Mobile-Experts with Informative Hybrid-Capabilities Reasoning
When to Think, When to Speak: Learning Disclosure Policies for LLM Reasoning
Why Agentic Theorem Prover Works: A Statistical Provability Theory of Mathematical Reasoning Models
The Cylindrical Representation Hypothesis for Language Model Steering
Stability beyond Bounded Differences: Sharp Generalization Bounds under Finite $L_p$ Moments
Linearizing Vision Transformer with Test-Time Training
ZipMoE: Efficient On-Device MoE Serving via Lossless Compression and Cache-Affinity Scheduling
BEDTime: A Unified Benchmark for Automatically Describing Time Series
Interpretable Functional Koopman Learning with Non-Markovian Closure for Spatiotemporal Systems
UniRRM: Unified Reasoning Reward Models Across Languages and Evaluation Paradigms
From Conflict to Consensus: Boosting Medical Reasoning via Multi-Round Agentic RAG
mSOP-765k: A Benchmark For Multi-Modal Structured Output Predictions
From Text to Forecasts: Bridging Modality Gap with Temporal Evolution Semantic Space
XTransfer: Modality-Agnostic Few-Shot Model Transfer for Human Sensing at the Edge
Quantifying Biases in LLM-as-a-Judge Evaluations
AudioMosaic: Contrastive Masked Audio Representation Learning
UMEM: Unified Memory Extraction and Management Framework for Generalizable Memory
AdaMEM: Test-Time Adaptive Memory for Language Agents
Optimal Decision-Making Based on Prediction Sets
Semantic Robustness Certification for Vision-Language Models
MAMBO-G: Magnitude-Aware Mitigation for Boosted Guidance
Sparse and Faithful Local Explanations with Piecewise Linear Surrogates
Proximal Splitting Methods for Hybrid Differentiable Models
On the Robustness of Langevin Dynamics to Score Function Error
Ambient Dataloops: Generative Models for Dataset Refinement
SPEED-Bench: A Unified and Diverse Benchmark for Speculative Decoding
Interleaved Selective State Space Models for Efficient WiFi-Based 3D Multi-Person Pose Estimation
Robust Linear Dueling Bandits with Post-serving Context under Unknown Delays and Adversarial Corruptions
Neural Logistic Bandits
MalTree: Tracing Malware Evolution using Embeddings at Scale
LIVEditor-14B: Lightning Unified Video Editing via In-Context Sparse Attention
AdaEraser: Training-Free Object Removal via Adaptive Attention Suppression
Don't Drop Dropout: Optimizing Layer Sparsity for Efficient LLM Training and Inference
FlashOptim: Memory Efficient Optimizers for Large-Scale Training
Geometric and Stochastic Analysis of Discontinuities in Sparse Mixture-of-Experts
Dynamic High-Dimensional Facility Location with Low Recourse
Improved Analysis of the Accelerated Noisy Power Method with Applications to Decentralized PCA
Infinite-Precision Autoregressive Modeling for Vector Graphics and Layouts
$\sigma$: Sigmoid Modulation for Ultra High Resolution Diffusion
DTop-p MoE: Sparsity-Controlled Dynamic Top-p MoE for Foundation Model Pre-training
A Factorized Low-Rank RNN Framework for Uncovering Independent Neural Latent Dynamics and Connectivity
FedEBA+: Towards Fair and Effective Federated Learning via Entropy-Based Model
HypoSpace: A Diagnostic Benchmark for Set-Valued Hypothesis Generation under Underdetermination and Sublinear Coverage Bounds
Regime-Adaptive Bayesian Optimization via Dirichlet Process Mixtures of Gaussian Processes
TraceRouter: Robust Safety for Large Foundation Models via Path-Level Intervention
Temporal-Emerged Prompting for Segment Anything in Multiframe Infrared Small Target Detection
Task-Driven Subspace Decomposition for Knowledge Sharing and Isolation in LoRA-based Continual Learning
WhisperSplat: Lossless Steganography in 3D Gaussian Splatting
Uncovering the Latent Potential of Deep Intermediate Representations
Forward-KL Convergence of Time-Inhomogeneous Langevin Diffusions
Let Language Constrain Geometry: Vision–Language Models as Semantic and Spatial Critics for 3D Generation
LS$^{2}$MC-GDA: A Smoothed Algorithm for Federated Stochastic Multi-Level Compositional Minimax Optimization
RECAST: Model Reconstruction via Counterfactual-Aware Wasserstein Geometry under Limited Data
Conditionally Site-Independent Neural Evolution of Antibody Sequences
Coverage, Not Averages: Semantic Stratification for Trustworthy Retrieval Evaluation
Reverse Flow Matching: A Unified Framework for Online Reinforcement Learning with Diffusion and Flow Policies
Knowing Bias, Doing Better: Mitigating Social Bias in LLMs via Know-Bias Neuron Enhancement
Breaking the Echo Chamber: A Dynamic Ensemble Pruning Perspective on MoE
Distilling Neuro-Symbolic Programs into 3D Multi-modal LLMs
Interpretability and Generalization Bounds for Learning Spatial Physics
ThunderAgent: A Fast, Simple, and Program-Aware Agentic Inference System
Position: Stop Anthropomorphizing Intermediate Tokens as Reasoning/Thinking Traces!
Continuous Viewpoint Adaptation for Single View 3D Object Reconstruction
InfoAtlas: A Foundation Model for Zero-Shot Statistical Dependence Estimate
Do Language Models Track Entities Across State Changes?
Less is More: Geometric Unlearning for LLMs with Minimal Data Disclosure
TGV-KV: Text-Grounded KV Eviction for Vision-Language Models
Functional Equivalence in Attention: A Comprehensive Study with Applications to Linear Mode Connectivity
Simple yet Effective: Low-Rank Spatial Attention for Neural Operators
From Inpainting to Editing: Unlocking Robust Mask-Free Visual Dubbing via Generative Bootstrapping
Human-in-the-Loop Policy Optimization for Preference-Based Multi-Objective Reinforcement Learning
SMD: Multi-view Safety-Critical Driving Video Generation in the Real-world Domain
CocoRNA: Collective RNA Design with Cooperative Multi-agent Reinforcement Learning
Same Graph Cross-Task Transfer in GNNs: Protocols and Predictors
SplAttN: Bridging 2D and 3D with Gaussian Soft Splatting and Attention for Point Cloud Completion
PACE: Post-Causal Entropy Modeling for Learned LiDAR Point Cloud Compression
GradientStabilizer: Fix the Norm, Not the Gradient
Multilingual Unlearning in LLMs: Transfer, Dynamics, and Reversibility
Hyperbolic Associative Memory Networks
An Approximation Algorithm for Graph Label Selection
Sample Margin-Aware Recalibration of Temperature Scaling
Convergence Analysis of Decentralized Hessian-/Jacobian-Free Algorithm for Nonconvex Stochastic Bilevel Optimization
Information Flow Reveals When to Trust Language Models
Dywave: Event-Aligned Dynamic Tokenization for Heterogeneous IoT Sensing Signals
Learning in the Fisher Subspace: A Guided Initialization for LoRA Fine-Tuning
TopBench: A Benchmark for Implicit Predictive Reasoning in Tabular Question Answering
Mind-Omni: A Unified Multi-Task Framework for Brain-Vision-Language Modeling via Discrete Diffusion
Dissecting Post-Training: Uncovering the Complementary Roles of SFT and RL for Document Parsing
Statistical-Computational Trade-offs for Recursive Adaptive Partitioning Estimators
Do Neural Operators Forget Geometry? The Forgetting Hypothesis in Deep Operator Learning
Verifying Meta-Awareness via Predictive Rewards in Reasoning Models
Progressive Graph Structure Adjustment for Homophily Shift Adaptation
DARTS: Distribution-Aware Active Rollout Trajectory Shaping for Accelerating LLM Reinforcement Learning
Position: Agentic AI Is a Foreseeable Pathway to AGI
What Does Thompson Sampling Optimize?
Scalable Training of 3D Gaussian Splatting via Out-of-Core Optimization
Improving Explicit Dynamic Gaussian Splatting Optimization via Update Mixture
Manifold-Aligned Guided Integrated Gradients for Reliable Feature Attribution
Coordinated Disentanglement with Iterative Mode Discovery Under Hidden Correlations
SE-GA: Memory-Augmented Self-Evolution for GUI Agents
Attention Implements the Fisher Geometry of Exponential Families
OvisOCR: End-to-End Document Parsing via Aligning Specialized Perception with General Reasoning
Denoising without Diffusion: Fixed-Noise Denoiser Anomaly Detection in Tabular Data
Context Distillation Retains Post-Training Capabilities in Continually Trained LMs
Are LLM Evaluators Really Narcissists? Sanity Checking Self-Preference Evaluations
HiPER: Hierarchical Plan–Execute RL for Multi-Turn LLM Agents
Hierarchical Filtering and Refinement Classification for Few-Shot Class-Incremental Learning
Jailbreak to Protect: Buffering Harmful Fine-Tuning via Temporary Jailbreaking LoRA in Large Language Models
Poison with Style: A Practical Poisoning Attack on Code Large Language Models
LLawCo: Learning Laws of Cooperation for Modeling Embodied Multi-Agent Behavior
Hyperbolic neural population geometry benefits computation
Many-Shot CoT-ICL: Making In-Context Learning Truly Learn
Learning from Fine-Grained Visual Discrepancies: Mitigating Multimodal Hallucinations via In-Context Visual Contrastive Optimization
Sparse ActionGen: Accelerating Diffusion Policy with Real-time Pruning
Cost-aware Stopping for Bayesian Optimization
SorryDB: Can AI Provers Complete Real-World Lean Theorems?
Possibilistic Predictive Uncertainty for Deep Learning
Characterizing Vision-Language-Action Models across XPUs: Constraints and Acceleration for On-Robot Deployment
HOBIT: Hardness Optimized Batch Sampling for InfoNCE Training
$\tau$-Voice: Benchmarking Full-Duplex Voice Agents on Real-World Domains
Understanding Deep Representation Learning via Layerwise Feature Compression and Discrimination
Latent Reasoning VLA: Latent Thinking and Prediction for Vision-Language-Action Models
Position: AI Usage Policies Should Be Aligned with International Human Rights Law
UGround: Towards Unified Visual Grounding with Unrolled Transformers
Modeling Hierarchical Thinking in Large Reasoning Models
When More Experts Hurt: Underfitting in Multi-Expert Learning to Defer
Self-Prophetic Decoding to Unlock Visual Search in LVLMs
Embodied Interpretability: Linking Causal Understanding to Generalization in Vision-Language-Action Models
Position: Prioritize Identifying Structure, Not Complex Models, for Scientific Discovery
NavOL: Navigation Policy with Online Imitation Learning
NeurVLA: Unleashing Failure-Handling Capability of Vision-Language-Action Models via Neural-Symbolic Reasoning
New Wide-Net-Casting Jailbreak Attacks Risk Large Models
Minimax-Optimal Policy Regret in Partially Observable Markov Games
Bio-Vision-Inspired Spiking Neural Networks for Object Detection with Event Cameras
HVAE: Hyperbolic Variational Autoencoder For Flexible Knowledge Transfer Across Multiple Domains
Domain Adaptation with Adaptive $f$-Divergence: Tighter Variational Representation and Generalization Bounds
Mitigating Hallucinations in Large Vision-Language Models via Causal Route Gating
Envy-Free Allocation of Indivisible Goods via Noisy Queries
Revisiting Asymmetries in Black-box Link Stealing against Graph Neural Networks
Prior Diffusiveness and Regret in the Linear-Gaussian Bandit
The Mechanistic Emergence of Symbol Grounding in Language Models
RePack then Refine: Efficient Diffusion Transformers with Vision Foundation Models
Beyond Next-Token Alignment: Distilling Multimodal Large Language Models via Token Interactions
Extending Mean-Field Variational Inference via Entropic Regularization: Theory and Computation
Linguistic Nepotism: Trading-off Quality for Language Preference in Multilingual RAG
Mean Flow Policy Optimization
TD3B: Transition-Directed Discrete Diffusion for Allosteric Binder Generation
Amodal Instance Segmentation with IRAIS Dataset for Sim-to-Real Transfer
All ERMs Can Fail in Stochastic Convex Optimization Lower Bounds in Linear Dimension
Black-Box Detection of LLM-Generated Text Using Generalized Jensen Shannon Divergence
Position: Multi-Agent Explainability Needs Contracts Before Methods
Decoupling Regularization and Privacy in Differentially Private Ridge Regression and ERM
Optimizing Rank for High-Fidelity Implicit Neural Representations
Exact Functional ANOVA Decomposition for Categorical Inputs
PLaID++: A Preference Aligned Language Model for Targeted Inorganic Materials Design
STEP: Warm-Started Visuomotor Policies with Spatiotemporal Consistency Prediction
Convex Low-resource Accent-Robust Language Detection in Speech Recognition
Copula-SVI: Vine-Copula Variational Inference with Stein Refining for Instance-Level Correlation Capturing
LARA: Latent Action Representation Alignment for Vision-Language-Action Models
DAPD: Dependency-Aware Parallel Decoding via Attention for Diffusion LLMs
Revisiting Padded Transformer Expressivity: Which Architectural Choices Matter and Which Don't
Deep Scientific Reasoning under Physical Constraints: Structure-Aware Spectrum Prediction
Corruption-Tolerant Asynchronous Q-Learning with Near-Optimal Rates
AppWorld-UL: Benchmarking Diverse Agent-User Interactions for Tool-Use
Less Diverse, Less Safe: The Indirect But Pervasive Risk of Test-Time Scaling in Large Language Models
Position: Machine Learning Research Should Be Guided by Explicit, Pluralistic Models of Human Purpose
FourTune: Towards Fully 4-Bit Efficient Post-Training for Diffusion Models
Localize-and-Stitch: Efficient Model Merging via Sparse Task Arithmetic
Optimality of FSQ Tokens for Continuous Diffusion for Categorical Data with Application to Text-to-Speech
HELIX: Hybrid Encoding with Learnable Identity and Cross-dimensional Synthesis for Time Series Imputation
WS-GRPO: Weakly-Supervised Group-Relative Policy Optimization for Rollout-Efficient Reasoning
Constrained Bayesian Experimental Design via Online Planning
Error Propagation Mechanisms and Compensation Strategies for Quantized Diffusion Models
One-step Optimal Transport via Regularized Distribution Matching Distillation
BroRL: Scaling Reinforcement Learning via Broadened Exploration
Protein Circuit Tracing via Cross-layer Transcoders
Decompose, Structure, and Repair: A Neuro-Symbolic Framework for Autoformalization via Operator Trees
Position: Preregister Experiments with AI Agents
DISSOLVR: An Interpretable and Fast Framework for Aqueous and Organic Solubility Prediction
Neural Feature Geometry Evolves as Discrete Ricci Flow
UniJEPA: Enhancing Robot Policy via Unified Continuous and Discrete Representation Learning
SE(n)-Invariant Flow Matching: A General Framework with Application to Object Reassembly
Hierarchical Retrieval at Scale: Bridging Interpretability and Efficiency
G2D2: Gradient-Guided Discrete Diffusion for Inverse Problem Solving
DRIVE: Distributional and Retrieval-Augmented Bidding with Value Evaluation
Causal Detection of Multi-Step LLM Agent Attacks
Functional Attention: From Pairwise Affinities to Functional Correspondences
Position: Measuring Human Preferences in RLHF is a Social Science Problem
LiME: Lightweight Mixture of Experts for Efficient Multimodal Multi-task Learning
RA-Det: Towards Universal Detection of AI-Generated Images via Robustness Asymmetry
Salus: Strategic Diagnostic Testing for Complex Diagnosis via Multi-Agent Reinforcement Learning
Monitoring Monitorability
Less Is More: Fast and Accurate Reasoning with Cross-Head Unified Sparse Attention
TadA-Bench: A Million-Variant Benchmark for Future-Round Discovery Toward Agentic Protein Engineering
Insertion Based Sequence Generation with Learnable Order Dynamics
The Geometry of Sequential Learning: Lie-Bracket Prediction of Transfer Order
Spatial Deconfounder: Interference-Aware Deconfounding for Spatial Causal Inference
Position: The Turing-Completeness of Real-World Autoregressive Transformers Relies Heavily on Context Management
Non-Stationary Online Structured Prediction with Surrogate Losses
Learning to Bet for Horizon-Aware Anytime-Valid Testing
Automata-Conditioned Cooperative Multi-Agent Reinforcement Learning
A²RBench: An Automatic Paradigm for Formally Verifiable Abstract Reasoning Benchmark Generation
Motion-Aware Caching for Efficient Autoregressive Video Generation
Position: RL Should Be Used to Adjust Foundation Models, NOT Abused
ECA: Efficient Continual Alignment for Open-Ended Image-to-Text Generation
Decentralized and Disentangled Task–Role Representation Learning for Generalizable Offline Multi-Agent Meta Reinforcement Learning
Fine-Tuning of Transformer models with Frames
Spectral-Informed Neural Networks Outperform Spectral methods in High-dimensional PDEs
LieStoNet: Learning Lie Symmetries from Spatiotemporal Data for Stochastic Dynamical Systems
DDGA: Dirichlet Distributional Gradient Aggregation for Transferable Vision-Language Adversarial Attacks
Multi-Head Attention as a Source of Catastrophic Forgetting in MoE Transformers
Negatives-Dominant Contrastive Learning for Generalization in Imbalanced Domains
PICACO: Pluralistic In-Context Value Alignment via Total Correlation Optimization
Towards Understanding Generalization of Federated Adversarial Learning: Perspective of Algorithmic Stability
Selective Coupling of Decoupled Informative Regions: Masked Attention Alignment for Data-Free Quantization of Vision Transformers
How RL Unlocks the Aha Moment in Geometric Interleaved Reasoning
Near-Minimax Multi-Objective RL under Predictable Adversarial Preferences and Preference-Free Exploration in Linear MDPs
Hierarchical Successor Representation for Robust Transfer
Position: Fairness Failure in Generative Models is an Evaluation Problem
Mind Your Margin and Boundary: Are Your Distilled Datasets Truly Robust?
CURVE: Learning Causality-Inspired Invariant Representations for Robust Scene Understanding via Uncertainty-Guided Regularization
Towards Spectroscopy: Susceptibility Clusters in Language Models
Less Precise Can Be More Reliable: A Systematic Evaluation of Quantization’s Impact on VLMs Beyond Accuracy
LiteVSR: Lightweight Adaptation of Frozen Diffusion Transformers for Video Super-Resolution
Rethinking Memory in Continual Learning: Beyond a Monolithic Store of the Past
Finite and Corruption-Robust Regret Bounds in Online Inverse Linear Optimization under M-Convex Action Sets
TVDRNet: Text-driven Viewpoint Optimization via Differentiable Rendering for 3D Reasoning Segmentation
Not All Rollouts are Useful: Down-Sampling Rollouts in LLM Reinforcement Learning
Reinforcement-aware Knowledge Distillation for LLM Reasoning
Chamaileon: Cross-Context Binder Design with Contextualized Modeling and Mixed Sampling
Hedging on the frontier: Learning new tasks with few samples
TranX-Adapter: Bridging Artifacts and Semantics within MLLMs for Robust AI-generated Image Detection
Target-Oriented Pretraining Data Selection via Neuron-Activated Graph
Position: AI Welfare Is Bullshit
Spatially-Regularized Entropy for Discriminative Token Merging in Fine-Grained Re-Identification
Position: Interestingness is an Inductive Heuristic for Future Compression Progress
Position: Breaking the Dual Curse of Multilingual AI Requires Socio-Technical Guardrails, Not Post-Hoc Alignment
Position: AI Lock-In Is in Progress, and We Must Be Prepared
Position: Temporal Measurement Interval Determines Computational and Model Complexity in Single-Cell Perturbation Analysis
Temporal Straightening for Latent Planning
Position: Stop Chasing the C-index when Evaluating Survival Analysis Models
MutAtlas: A PDB-Wide Energy-Guided Atlas of Protein Mutation Effects
Position: We Need Practical AI Alignment Methods that Mirror Human Reasoning
CamGeo: Sparse Camera-Conditioned Image-to-Video Generation with 3D Geometry Priors
Position: Video LLMs Must Not Ignore the Pixel Dynamics in Plain Sight
ECHO: Elastic Speculative Decoding with Sparse Gating for High-Concurrency Scenarios
Learning Rate Annealing Improves Tuning Robustness in Stochastic Optimization
Position: Retire the "Positive Backdoor" Label—Secret Alignment Requires Strict and Systematic Evaluation
Position: the Stochastic Parrot in the Coal Mine. Model Collapse is a Threat to Low-Resource Communities
Procedural Generation Of Algorithm Discovery Tasks in Machine Learning
Position: Agentic Systems Should be General
Position: Time-Series Foundation Models Require Explicit Domain-Level Benchmarks
Position: Vision encoders should be image size agnostic and task driven
Beyond Independent Genes: Learning Module-Inductive Representations for Single-Cell Gene Perturbation Prediction
Position: Collusion Risks Among AI Reasoning Agents Justify Certification Requirements for Making Market Decisions
Position: AI Governance Needs ISO-like Interoperability Protocols, Not Just Laws
Position: There are futures that benchmark-driven AI cannot see
On the Variability of Concept Activation Vectors
Position: We need to re-think the concept of “real” images.
Position: Trustworthy AI Suffers from Invariance Conflicts and Causality is The Solution
ReflFlow: Learning Geometry-Guided Ray Tracing for Dynamic Specular Reconstruction
Position: Let's Develop Data Probes to Fundamentally Understand How Data Affects LLM Performance
Position: Evaluation of ECG Representations Must Be Fixed
Are Two Datasets Close Enough With Statistical Significance? A Kernel Distributional Closeness Testing Approach
Position: Peer Review Should Be Calibrated via LLM Scoring
Position: Embodied AI Requires a Privacy-Utility Tradeoff
Position: Virtual Cells Need Context, Not Just Scale
GRAPE: Let GRPO Supervise Query Rewriting by Ranking for Retrieval
Position: VLM Causal Reasoning Benchmarks Should Probe Temporal Understanding, Not Presume It
Position: Sustainable Open-Source AI Requires Tracking the Cumulative Footprint of Derivatives
Implicit Safety Alignment from Crowd Preferences
Instruction Decomposition and Action Alignment for Vision-Language Navigation
Position: RL Researchers Need to Distinguish Between Solving Simulators and Using Simulators as a Proxy
Generative Modeling of Irregular Time Series via SDE-Induced Continuous-Discrete Variational Inference
ORLoopBench: Solver-in-the-Loop Benchmarks for Self-Correction and Behavioral Rationality in Operations Research
Position: Stop Reactively Patching Your Model Every Time and Start Proactive Test-Driven AI Development
Position: AI Should Facilitate Democratic Deliberation at Scale
Position: Safety Must Precede the Deployment of Open-Ended AI Agents
Adaptive Bandit Algorithms for Contextual Matching Markets
Position: Graph Condensation Needs a Reset—Move Beyond Full-dataset Training and Model-Dependence
SSDCN: Spatial-Spectral Dual-Clustering-based Network for Hyperspectral Image Super-resolution
Position: Safe AI Should be Resistant and Resilient in an Evolving World
VCG-Bench: Towards A Unified Visual-Centric Benchmark for Structured Generation and Editing
Position: Early-Stage Quality Assurance in Annotation Pipelines Is More Cost-Effective Than Late-Stage Validation
Action-Sufficient Goal Representations
From Blind Spots to Gains: Diagnostic-Driven Iterative Training for Large Multimodal Models
Position: Machine Learning for Heart Transplant Allocation Policy Optimization Should Account for Incentives
Position: Agent Should Invoke External Tools ONLY When Epistemically Necessary
What Do Agents Learn from Trajectory-SFT: Semantics or Interfaces?
Position: The Open Benchmark Paradox Must Be Resolved through Sovereign Medical Evaluation
Near-Optimal Dynamic Matching via Coarsening with Application to Heart Transplantation
Position: Deciphering the Functions of DNAs, RNAs, and Proteins Should Consider Multi-Modal Large Language Models
On Computation and Reinforcement Learning
InteractComp: Evaluating Search Agents With Ambiguous Queries
ScreenParse: Moving Beyond Sparse Grounding with Complete Screen Parsing Supervision
Predicting Large Model Test Losses with a Noisy Quadratic System
Position: Make Planning Research Rigorous Again!
Position: Improved Documentation is Necessary for Benchmarking AI Systems in Geometry
Position: State-of-the-Art Claims Require State-of-the-Art Evidence
ABC-Bench: An Agentic Bio-Capabilities Benchmark for Biosecurity
Distribution Transformers: Fast Approximate Bayesian Inference With On-The-Fly Prior Adaptation
Real-World Unsupervised Models Generalize to Predict Brain Responses to Out-of-Distribution Stimuli
Attention Sparsity is Input-Stable: Training-Free Sparse Attention for Video Generation via Offline Sparsity Profiling and Online QK Co-Clustering
Agent0-VL: Exploring Self-Evolving Agent for Tool-Integrated Vision-Language Reasoning
When Does Adaptation Win? Scaling Laws for Meta-Learning in Quantum Control
Retriever Portfolios: A Principled Approach to Adaptive RAG
Domain Restriction via SAE Multi-Layer Transitions
When Attributes Disagree: Gradient Conflict in Image Aesthetic Assessment
Robust Filter Attention: Self-Attention as a Parallel State Estimator
Mixture of Horizons in Action Chunking
Attention Illuminates LLM Reasoning: The Uncovered Preplan-and-Anchor Rhythm Enables Fine-Grained Policy Optimization
A Computational Framework for Evaluating Human-likeness in LLMs' Open-ended Human Behaviors
Contextualized Privacy Defense for LLM Agents
Position: Multi-Agent Systems Should Prioritize Concurrency Control
LFQ: Logit-aware Final-block Quantization for Boosting the Generation Quality of Low-Bit Quantized LLMs
The Geometric Origin of Grokking: Accelerating Generalization via Active Structural Reorganization
SleepLM: Natural-Language Intelligence for Human Sleep
Optimal Learning from Label Proportions with General Loss Functions
Optimal structure learning and conditional independence testing
LaTtE-Flow: Layerwise Timestep-Expert Flow-based Transformer
Testing For Distribution Shifts with Conditional Conformal Test Martingales
General Synthetic-Powered Inference
PaperBanana: Automating Academic Illustration for AI Scientists
Activation-Free Backbones for Image Recognition: Polynomial Alternatives within MetaFormer-Style Vision Models
Guaranteed Optimal Compositional Explanations for Neurons
PRISM: Perception Reasoning Interleaved for Sequential Decision Making.
OC-space: a Unifying Perspective on Verification of Tree Ensembles
SJD-SV: Speculative Jacobi Decoding with Semantics Verification for Autoregressive Image Generation
FRISM: Fine-Grained Reasoning Injection via Subspace-Level Model Merging for Vision–Language Models
Who Said Neural Networks Aren't Linear?
Why Self-Distillation Helps and Hurts: Denoising vs. Signal Forgetting
ACTIVE-o3 : Empowering MLLMs with Active Perception via Pure Reinforcement Learning
Improved Dimension Dependence for Bandit Convex Optimization with Gradient Variations
Mixtures of geodesic factor analyzers on Riemannian homogeneous spaces
Singular Vectors of Attention Heads Align with Features
Beyond Two-Stage Training: Cooperative SFT and RL for LLM Reasoning
Learning Molecular Semantic Invariant Representation with Prototype Constraint
Control Consistency Losses for Diffusion Bridges
ViSurf: Visual Supervised-and-Reinforcement Fine-Tuning for Large Vision-and-Language Models
PASO: Step Parallel Stochastic Optimization
Joint Learning in the Gaussian Single Index Model
You Don’t Need All That Attention: Surgical Memorization Mitigation in Text-to-Image Diffusion Models
Linear Regression with Unknown Truncation Beyond Gaussian Features
An Information-Theoretic Criterion for Efficient Data Synthesis
SparseSSM: Efficient Selective Structured State Space Models Can Be Pruned in One-Shot
Riemannian MeanFlow for One-Step Generation on Manifolds
Towards Solving the Gilbert-Pollak Conjecture via Large Language Models
Reward Hacking Benchmark: Measuring Exploits in LLM Agents with Tool Use
Coupled Training with Privileged Information and Unlabeled Data
Quantifying Frontier LLM Capabilities for Container Sandbox Escape
Hallucination Detection from Structural Reasoning Model
Towards Fair Sequential Decision-Making: A Causal Decomposition Approach
A Control-Theoretic View of Mamba on Stability and Robustness
Transformed Latent Variable Multi-Output Gaussian Processes
Causal Feature Learning via Generalized Rayleigh Quotients
Position: Benchmarks Do Not Measure Deployment Readiness in Clinical AI
Diff-MN: Diffusion Parameterized MoE-NCDE for Continuous Time Series Generation with Irregular Observations
From Bits to Rounds: Parallel Decoding with Exploration for Diffusion Language Models
MAD: Manifold Attracted Diffusion
Preconditioning Neural Tangent Kernel for Adaptive Optimization
ABCD: All Biases Come Disguised
Enhancing Conformal Prediction via Class Similarity
Mechanisms of Introspective Awareness
Active Curriculum Refinement for Reinforcement Learning
Bayes-inspired Integration of Pretrained Priors and Few-Shot Evidence for Few-Shot Classification
RLVE: Scaling Up Reinforcement Learning for Language Models with Adaptive Verifiable Environments
SOPE: Situation-Aware and Statistically Indistinguishable Privacy Exfiltration for MCP-enabled Agents
The Value of Variance: Mitigating Debate Collapse in Multi-Agent Systems via Uncertainty-Driven Policy Optimization
DyGRO-VLA: Cross-Task Scaling of Vision–Language–Action Models via Dynamic Grouped Residual Optimization
Jailbreak Foundry: From Papers to Runnable Attacks for Reproducible Benchmarking
Panini: Continual Learning in Token Space via Structured Memory
Return-to-Go Is More Than a Number: Q-Guided Alignment for Return-Conditioned Supervised Learning
Beyond Logits: Metastable Latent Dynamics for Sample-Efficient Best-of-N Selection in LLMs
Dismantling Pathological Shortcuts: A Causal Framework for Faithful LVLM Decoding
NeUQI: Near-Optimal Uniform Quantization Parameter Initialization for Low-Bit LLMs
Influence-Guided Symbolic Regression: Scientific Discovery via LLM-Driven Equation Search with Granular Feedback
Does a Hybrid Space-Aware Randomized Defense Improve Empirical and Certified Adversarial Robustness?
From Kepler to Newton: Inductive Biases Guide Learned World Models in Transformers
DropoutTS: Sample-Adaptive Dropout for Robust Time Series Forecasting
Decomposing Out-of-Distribution Error in Conditional Flow Matching via Wasserstein Geometry
Alleviating Sparse Rewards by Modeling Step-Wise and Long-Term Sampling Effects in Flow-Based GRPO
Efficient Synthetic Network Generation via Latent Embedding Reconstruction
Learning to Think in Physics: Breaking Shortcut Learning in Scientific Diffusion via Representation Alignment
Batched First-Order Methods for Parallel LP Solving in MIP
High-accuracy sampling for diffusion models and log-concave distributions
Search or Accelerate: Confidence-Switched Position Beam Search for Diffusion Language Models
DLM: Unified Decision Language Models for Offline Multi-Agent Sequential Decision Making
Future-Gain Guided Test-Time Learning for Large Language Models
Evaluating the Representation Space of Diffusion Models via Self-Supervised Principles
What Preferences Can—and Cannot—Predict in Multi-Agent Online Learning
On the Optimization Trajectory of DeepWalk Embeddings
AdaNav: Adaptive Reasoning with Uncertainty for Vision-Language Navigation
Reward Under Attack: Analyzing the Robustness and Hackability of Process Reward Models
DOT-MoE: Differentiable Optimal Transport for MoEfication
SWING: Unlocking Implicit Graph Representations for Graph Random Features
Towards Pareto-Optimal Tool-Integrated Agents with Pareto Ranking Policy Optimization
AVGen-Bench: A Task-Driven Benchmark for Multi-Granular Evaluation of Text-to-Audio-Video Generation
World-R1: Reinforcing 3D Constraints for Text-to-Video Generation
All Circuits Lead to Rome: Rethinking Functional Anisotropy in Circuit and Sheaf Discovery for LLMs
SpanNorm: Reconciling Training Stability and Performance in Deep Transformers
From Memorization to Parameter Interference: How Overtraining Experts Harms Model Merging
daVinci-Dev: Agent-native Mid-training for Software Engineering
Demystifying When Pruning Works via Representation Hierarchies
Agora: Toward Autonomous Bug Detection in Production-Level Consensus Protocols with LLM Agents
Position: Scale is a False Promise for Endangered Languages
FluxNet: Learning Capacity-Constrained Local Transport Operators for Conservative and Bounded PDE Surrogates
FlowCloud: Learning Continuous Spatiotemporal Dynamics from Unpaired Sparse Point Cloud Snapshots
PhenoBrain: Phenotype-Conditioned Long-Range Communication for Multi-Modal Brain Network Analysis
State Space Model with Continuous Limit of HiPPO Matrix: Eigenvalue Analysis and Explicit Solution Formula
Reasoning over Boundaries: Enhancing Specification Alignment via Test-time Deliberation
BAT: Better Audio Transformer Guided by Convex Gated Probing
Toward Cybersecurity-Expert Small Language Models
Trust Functions: Near Lossless Weak-to-Strong Generalization by Learning to Trust the Weak Teacher
Characterizing, Evaluating, and Optimizing Complex Reasoning
Efficient Continuous-Depth Modeling with GRU Equivalents
Position: Adopting AI in Practice Does Not Guarantee the Productivity Boost
Turning Back Without Forgetting: Selective Backward Refinement for Parameter-Efficient Continual Learning
Scaling Beyond Masked Diffusion Language Models
An In-Depth Study on Deep Learning Model Cloning
PrivGate: Steering Contextual Integrity in LLMs via Latent Space Geometry
CameraNoise: Enabling Faithful Camera Control in Video Diffusion through Geometry-Flow-Guided Noise Warping
The Sign Estimator: Preference Modeling for LLM Alignment under Heterogeneity
The Geometry of Updates: Fisher Alignment at Vocabulary Scale
Scaling Generative Verifiers For Natural Language Mathematical Proof Verification And Selection
Softplus Attention with Re-weighting Boosts Length Extrapolation in Large Language Models
Q-Flow: Stable and Expressive Reinforcement Learning with Flow-based Policy
Universal Redundancies in Time Series Foundation Models
Time Series, Vision, and Language: Exploring the Limits of Alignment in Contrastive Representation Spaces
PretrainZero: Reinforcement Active Learning on Pretraining Data
GSRQ: Gain-Shape Residual Quantization for Sub-1-bit KV Cache
Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective
ProEval: Proactive Failure Discovery and Efficient Performance Estimation for Generative AI Evaluation
Position: From Crowdsourcing to Crowd-LLM-Sourcing and LLM-Sourcing
SuperHype: Hypergraph Generation via Graph-Superposition Decomposition
See First, Reason Later: Mutual Information-Guided Reinforcement Learning for Vision-Language Models
An Efficient Joint Learning Approach for Item Response Theory
Learning Normalized Energy Models for Linear Inverse Problems
On the Salience of Low-Probability Tokens for AI-Generated Text Detection: A Multiscale Uncertainty Perspective
Training-Free Coverless Multi-Image Steganography with Access Control
Symmetries in PAC-Bayesian Learning
Formalizing the Binding Problem
Required Spine Optional Limbs: Heterogeneous Federated Learning via Backbone-sharing and Activation-guided Selection
RoboTwin 2.0: A Scalable Data Generator and Benchmark with Strong Domain Randomization for Robust Bimanual Robotic Manipulation
Asymptotic Optimality of the High-Dimensional Gaussian Mechanism and Improved Low-Dimensional Mechanisms for Differential Privacy
Decentralized Instruction Tuning: Conflict-Aware Splitting and Weight Merging
A Positive Case for Faithfulness: Explanations Help Predict Model Behavior
Intrinsic Credit Assignment for Long Horizon Interaction
Evolution of Benchmark: Black-Box Optimization Benchmark Design through Large Language Model
Robust Causal Discovery in Real-World Time Series with Power-Laws
Strategic Navigation or Stochastic Search? How Agents and Humans Reason Over Document Collections
Turning Bias into Bugs: Bandit-Guided Style Manipulation Attacks on LLM Judges
A Queueing-Theoretic Framework for Stability Analysis of LLM Inference with KV Cache Memory Constraints
$\alpha$-PFN: Fast Entropy Search via In-Context Learning
Stochastic Gradient Variational Inference with Price's Gradient Estimator from Bures-Wasserstein to Parameter Space
How Does the Lagrangian Guide Safe Reinforcement Learning through Diffusion Models?
How does Chain of Thought decompose complex tasks?
AIR: Improving Agent Safety through Incident Response
TG-RAG: A Retrieval-Augmented Framework for Reasoning Guidance in Specialized Domains
Solving the Offline and Online Min-Max Problem of Non-smooth Submodular-Concave Functions: A Zeroth-Order Approach
It's a TRAP! Task-Redirecting Agent Persuasion Benchmark for Web Agents
Robust Bayes-Assisted Conformal Prediction
SpeedCP: Fast Kernel-based Conditional Conformal Prediction
Optimizing Return Distributions with Distributional Dynamic Programming
Understanding Performance Collapse in Layer-Pruned Large Language Models via Decision Representation Transitions
Token-Free Hierarchical Indexing for RAG beyond LLM-based Summarization
Demystifying MaskGIT Sampler and Beyond: Adaptive Order Selection in Masked Diffusion
Reasoning as an Attack Surface: Adaptive Evolutionary CoT Jailbreaks for LLMs
Quantum Robust Inner Minimization for Reinforcement Learning with Quadratic Speed-Up in Query Complexity
EntRAG: Entity-Centric Retrieval-Augmented Generation for Knowledge-based Visual Question Answering
Learning to Extrapolate to New Tasks: A Relational Approach to Task Extrapolation
Hierarchical ODE: Learning Continuous-Time Physical Prototypes for Early Link Failure Detection
mHC: Manifold-Constrained Hyper-Connections
Perceptrons and Localization of Attention’s Mean-Field Landscape
Divide and Conquer: Reliable Multi-View Evidential Learning for Deepfake Detection
SHAP-Guided Kernel Actor-Critic for Explainable Reinforcement Learning
Beyond Softmax: A Natural Parameterization for Categorical Random Variables
Reconstruction Outcomes Look Similar but Processes Differ: Improving Context Consistency and Coverage in Graph Masked Auto-Encoder
RelaxFlow: Text-Driven Amodal 3D Generation
Towards Steering without Sacrifice: Principled Training of Steering Vectors for Prompt-only Interventions
Activation Oracles: Training and Evaluating LLMs as General-Purpose Activation Explainers
AgentNoiseBench: Benchmarking Robustness of Tool-Using LLM Agents Under Noisy Condition
Laplacian Representations for Decision-Time Planning
From Abstraction to Instantiation: Learning Behavioral Representation for Vision-Language-Action Model
EPiC: Efficient Video Camera Control Learning with Precise Anchor-Video Guidance
Solving Time-Dependent Differential Equations with Physical Dynamical Systems
Position: Spatial Fairness: Foundations, Pitfalls, and a Path Forward
Position: Robust AI Personalization Will Require a Human Context Protocol
Ranking Time Series using a Time Warping Ideal Point Model
Divide and Contrast: Learning Robust Temporal Features without Augmentation
Capturing Gaze Shifts for Guidance: Cross-Modal Fusion Enhancement for VLM Hallucination Mitigation
PolyFlow: Safe and Efficient Polytope-Constrained Flow Matching with Constraint Embedding and Projection-free Update
SpecPL: Disentangling Spectral Granularity for Prompt Learning
Rare Event Analysis of Large Language Models
Analytic Bijections for Smooth and Interpretable Normalizing Flows
Predictive Prefetching for Retrieval-Augmented Generation
Target-Aware Bandit Allocation for Scalable Surrogate Optimization in Chemical Space
CPMöbius: Iterative Coach–Player Reasoning for Data-Free Reinforcement Learning
FedSSM: State Space Model-based Proactive Inference for Heterogeneous Multimodal Federated Learning
UAV$^2$: A Unified and Adaptive Scheduling Framework for UAV Autopilot System with Reinforcement Learning
Ensembling Sparse Autoencoders
Judgment Operators: A Composition-Invariant Substrate for Multi-Agent Action Spaces
Stability and Generalization of Nonconvex Optimization with Heavy-Tailed Noise
Unsafer in Many Turns: Benchmarking and Defending Multi-Turn Safety Risks in Tool-Using Agents
ACO-MoE-LoRA: Evolving-while-Training for Adapting Segment Anything Model 2 to Specialized Domains
What You Think is What You See: Driving Exploration in VLM Agents via Visual-Linguistic Curiosity
UniRTL: Unifying Code and Graph for Robust RTL Representation Learning
Position: Want Better ML Reviews? Stop Asking Nicely and Start Incentivizing with a Credit System
Position: Bridge Human Interpretation and Machine Representation With Explicit Specification For Qualitative Data Analysis In LLM Era
Scheduling LLM Inference with Uncertainty-Aware Output Length Predictions
RSA-CP: Efficient Conformal Prediction in Small-Sample Regimes via Random Score Alignment
Evaluating Relational Reasoning in LLMs with REL
Hom-PGD$^+$: Fast Reparameterized Optimization over Non-convex Ball-Homeomorphic Set
Iterative Refinement Neural Operators are Learned Fixed-Point Solvers: A Principled Approach to Spectral Bias Mitigation
Large Language Models Develop Novel Social Biases Through Adaptive Exploration
FlashBlock: Attention Caching for Efficient Long-Context Block Diffusion
StethoLM: Audio Language Model for Cardiopulmonary Analysis Across Clinical Tasks
Motion-Residual Conflict-Aware Time Reversal for Generative Inbetweening
Constrained Meta Reinforcement Learning with Provable Test-Time Safety
Unified Safe In-context Image Generation in Multimodal Diffusion Transformers via Restricting Unsafe Information Flows
Alignment-Sensitive Minimax Rates for Spectral Algorithms with Learned Kernels
Orchestrating Spatial Semantics via a Zone-Graph Paradigm for Intricate Indoor Scene Generation
Robust Harmful Features Under Jailbreak Attacks: Mechanistic Evidence from Attention Head Specialization in Large Language Models
Lookahead-GCG: Improving Universal Multi-Model Optimization-Based Jailbreaking Attacks via Stochastic Nesterov Optimization
SlaClip: Gradient Norm Slacks can be Indicator for Adaptive Clipping in DP-SGD
A Close Look at Negative Label Guided Out-of-distribution Detection in Pre-trained Vision-Language Models
Frontier Models Can Take Actions at Low Probabilities
Position: Weight Space Should Be a First-Class Generative AI Modality
Generalized Schrödinger Bridge on Graphs
Bridging On-Device and Cloud LLMs for Collaborative Reasoning: A Unified Methodology for Local Routing and Post-Training
Federated Sketching LoRA: A Flexible Framework for Heterogeneous Collaborative Fine-Tuning of LLMs
On Effectiveness and Efficiency of Agentic Tool-calling and RL Training
The Trojan Knowledge: Bypassing Commercial LLM Guardrails via Harmless Prompt Weaving and Adaptive Tree Search
Learning-to-Optimize via Deep Unfolded Flows
SCOPE and SCION: A Benchmark and an Auditable Reference Pipeline for Schema Induction and Fusion from Text
Federated Variational Preference Alignment with Gumbel-Softmax Prior for Personalized User Preferences
CARE: Confounder-Aware Aggregation for Reliable LLM Evaluation
A Kinetic-Energy Perspective of Flow Matching
Measuring Meta-Cultural Competency: A Spectral Framework for LLM Knowledge Structures
FOCUS & RePAIR: Mitigating Text Degeneration via Token-Level Guidance For Pruned Large Language Models
On the Collapse of Generative Paths: A Criterion and Correction for Diffusion Steering
Sem-Detect: Semantic Level Detection of AI Generated Peer-Reviews
Near-Optimal Private Linear Regression via Iterative Hessian Mixing
SVRG and Beyond via Posterior Correction
Position: Responsible Practices and Model Performance are Not Competing Goals
Position: Agent Evaluation Should Be Agentified for Openness, Standardization, and Reproducibility
VERA-V: Variational Inference Framework for Jailbreaking Vision-Language Models
Physiology-Aware Masked Cross-Modal Reconstruction for Biosignal Representation Learning
Multi-Integration of Labels Across Categories for Component Identification in Multi-trial Time Series
Sparse Bayesian Deep Functional Learning with Structured Region Selection
Understanding Self-Supervised Learning via Latent Distribution Matching
Hierarchical Abstract Tree for Cross-Document Retrieval Augmented Generation
Adversarial Flow Models
Data Provenance Auditing of Fine-Tuned Large Language Models with a Text-Preserving Technique
Visual Implicit Autoregressive Modeling
Split Group Knockoffs: Controlling False Discovery Rate in Transformational Group Sparsity
SHARP-Q: Spectral Hessian Alignment and Rectification for Post-training Quantization
Performative Policy Gradient: Optimality in Performative Reinforcement Learning
Adaptive Probe-based Steering for Robust LLM Jailbreaking
PragLocker: Protecting Agent Intellectual Property in Untrusted Deployments via Non-Portable Prompts
From geometry to dynamics: Learning overdamped Langevin dynamics from sparse observations with geometric constraints
Adversarial Attacks and Robust Training for Hypergraph Neural Networks
Wikipedia in the Era of LLMs: Evolution and Risks
Escaping the Diversity Trap in Robotic Manipulation via Anchor-Centric Adaptation
Do Sparse Autoencoders Identify Reasoning Features in Language Models?
Mitigating Staleness in Asynchronous Pipeline Parallelism via Basis Rotation
Incentivizing Truthfulness and Collaborative Fairness in Bayesian Learning
From Pixels to Tokens: A Systematic Study of Latent Action Supervision for Vision-Language-Action Models
INFER: Learning Implicit Neural Frequency Response Fields for Confined Acoustic Environments
Why Deep Jacobian Spectra Separate: Depth-Induced Scaling and Singular-Vector Alignment
Asymptotically Optimal Sequential Testing with Markovian Data
Q-Sched: Pushing the Boundaries of Few-Step Diffusion Models with Quantization-Aware Scheduling
LithoGRPO: Fast Inverse Lithography via GRPO Reinforced Flow Matching
Understanding Multimodal Learning: A Loss Landscape Smoothness Perspective
Beyond Log Likelihood: Probability-Based Objectives for Supervised Fine-Tuning across the Model Capability Continuum
Differential syntactic and semantic encoding in LLMs
HEDP: A Hybrid Energy-Distance Prompt-based Framework for Domain Incremental Learning
MathlibLemma: Folklore Lemma Generation and Benchmark for Formal Mathematics
Neural Thickets: Diverse Task Experts Are Dense Around Pretrained Weights
Multi-Task GRPO: Reliable LLM Reasoning Across Tasks
Semi-Supervised Hypothesis Testing by Betting on Predictions
Position: Creating High-Fidelity Synthetic Training Data Should Employ Multi-level Optimization
Improving Sampling for Masked Diffusion Models via Information Gain
Random Process Flow Matching: Generative Implicit Representations of Multivariate Random Fields
Mechanistic Anomaly Detection via Functional Attribution
Curated Synthetic Data Doesn’t Have to Collapse: A Theoretical Study of Generative Retraining with Pluralistic Preferences
Do Transformers Need Three Projections? Systematic Study of QKV Variants
ThreadWeaver: Adaptive Threading for Efficient Parallel Reasoning in Language Models
Colorful Pinball: Density-Weighted Quantile Regression for Conditional Guarantee of Conformal Prediction
Position: Causality is Key for Interpretability Claims to Generalise
Rethinking Neural Network Learning Rates: A Stackelberg Perspective
SafeSeek: Universal Attribution of Safety Circuits in Language Models
ViTok-v2: Scaling Native Resolution Autoencoders to 5 Billion Parameters
On the Fragility of Data Attribution When Learning Is Distributed
AlgoTrace: Algorithmic Primitives and Compositional Geometry of Reasoning in Language Models
Correctness-Optimized Residual Activation Lens (CORAL): Transferrable and Calibration-Aware Inference-Time Steering
Entropic Mirror Monte Carlo
Reason with Thumbnails, Answer with Focus: An Efficient and Effective Paradigm for Multimodal Grounded Visual Reasoning
MUSA-PINN: Multi-scale Weak-form Physics-Informed Neural Networks for Fluid Flow in Complex Geometries
Agentic Monte Carlo: Simulating Reinforcement Learning for Black-Box Agents
ContrastiveCFG: Guiding Diffusion Sampling by Contrasting Positive and Negative Concepts
An Interactive Paradigm for Deep Research
Diagnosing and Correcting Concept Omission in Multimodal Diffusion Transformers
Credible Information Subset Decomposition: An End-to-End Multi-fidelity Learning Model by Modeling Label Information
SymSpectra: Symmetric Information Bottleneck Framework for Molecular Structure Recognition under Imbalanced Settings
Broadening the Backdoor Basin: Understanding LLM Backdoors Collapse and Making Backdoors Persistent
Robust Contextual Optimization with Missing Covariates
Unsupervised Partner Design Enables Robust Ad-hoc Teamwork
Computational Arbitrage in AI Model Markets
BALLAST: Bayesian Active Learning with Look-ahead Amendment for Sea-drifter Trajectories under Spatio-Temporal Vector Fields
Pull Requests as a Training Signal for Repo-Level Code Editing
Position: World Models as an Intermediary between Agents and the Real World
Efficiently Solving Discounted MDPs via Predictions with Unknown Prediction Errors
RADE: Random Add-Drop Edge as a Regularizer
Rényi Diffusion Models
The Two-Hump Problem: Bridging the Difficulty Gap in Mathematical Reinforcement Learning
VideoMAETok: Boosting Video Diffusion Models via Masked Autoencoders as Tokenizers
Hierarchical Reinforcement Learning for Sparse-Reward Search in Commutative Algebra
Bottleneck Communication Delay Minimization for Communication-Efficient Decentralized Learning
Monotonic Variational Gaussian Process for Efficient Data Collection
Differentiable Optimization Layers for Guaranteed Fairness in Deep Learning
Masked Multi-path Contrast with Confidence-Gated Semantic Imputation for Incomplete Multi-view Clustering
Root Cause Analysis of Failures in Microservices via Bayesian Root Cause Discovery
Kronecker Generative Networks: A General Neural Architecture for Parameter-Efficient Learning Across Classification Tasks
Variable-Length Tokenization via Learnable Global Merging for Diffusion Transformers
AdverMCTS: Combating Pseudo-Correctness in Code Generation via Adversarial Monte Carlo Tree Search
AgentHijack: Benchmarking Computer Use Agent Robustness to Common Environment Corruptions
ML-Agent: Reinforcing LLM Agents for Autonomous Machine Learning Engineering
The Consistency Dilemma in LLMs: Generator-Evaluator Agreement and Vulnerability to Mistakes
MCP-Persona: Benchmarking LLM Agents on Real-World Personal Applications via Environment Simulation
Risk Awareness Injection: Calibrating Vision-Language Models for Safety without Compromising Utility
The Tell-Tale Norm: $\ell_2$ Magnitude as a Signal for Reasoning Dynamics in Large Language Models
Cross-Modal Semantic Decoupling and Transfer for Text-to-Visible-Infrared Person Re-Identification
MemoryLLM: Plug-n-Play Interpretable Feed-Forward Memory for Transformers
MoLoRA: Composable Specialization via Per-Token Adapter Routing
Singular Proxies for Adaptive Caching in Diffusion Language Models
Unleashing Implicit Rewards: Prefix-Value Learning for Distribution-Level Optimization
Revisiting the Bertrand Paradox via Equilibrium Analysis of No-regret Learners
When Model Merging Breaks Routing: Training-Free Calibration for MoE
Dissecting Multimodal In-Context Learning: Modality Asymmetries and Circuit Dynamics in modern Transformers
Context-level Language Modeling by Learning Predictive Context Embeddings
SOTAlign: Semi-Supervised Alignment of Unimodal Vision and Language Models via Optimal Transport
Cluster-Aware Causal Mixer for Online Anomaly Detection in Multivariate Time Series
A Dirac-Frenkel-Onsager principle: Instantaneous residual minimization with gauge momentum for nonlinear parametrizations of PDE solutions
Circle-RoPE: Cone-like Decoupled Rotary Positional Embedding for Vision-Language Models
Diamond Maps: Efficient Reward Alignment via Stochastic Flow Maps
Mantis: Lightweight Foundation Model for Time Series Classification
A geometric relation of the error introduced by sampling a language model's output distribution to its internal state
FLIPS: Instance-Fingerprinting for LLMs via Pseudo-random Sequences
A$^2$SG: Adaptive and Asymmetric Surrogate Gradients for Training Deep Spiking Neural Networks
Best of Both Worlds: Multimodal Reasoning and Generation via Unified Discrete Flow Matching
Hi-Time: Hierarchical Latent Prediction for Multivariate Time Series Classification
Learnability-Informed Fine-Tuning of Diffusion Language Models
Mitigating Manifold Departure: Uncertainty-Aware Subspace Rectification for Trustworthy MLLM Decoding
Retaining by Doing: The Role of On-Policy Data in Mitigating Forgetting
Mechanistic Data Attribution: Tracing the Training Origins of Interpretable LLM Units
Mitigating Gradient Pathology in PINNs through Aligned Constraint
U$^3$CF: Unbiased, Unconfounding, and Unified Causal Framework for Multi-Target Domain Adaptation
Adaptive Quasimetric Mapping : Principled Topological Abstraction for Robust Offline Goal-Conditioned Navigation
Find, Fix, Reason: Context Repair for Video Reasoning
Optimizing Network Simulation: Enhancing Performance Prediction Accuracy via Neural Architecture Search
Position: Human-Centric Vision Requires Topological Generalization Beyond Fixed Skeletal Topologies
Enhancing LLM Training via Spectral Clipping
Position: Preparing for AI Systems That Deceive Developers
CONCUR: High-Throughput Agentic Batch Inference of LLM via Congestion-Based Concurrency Control
Amortized Variational Inference for Partial-Label Learning: A Probabilistic Approach to Label Disambiguation
CoCoEmo: Composable and Controllable Human-Like Emotional TTS via Activation Steering
LLM-Guided Diagnostic Evidence Alignment for Medical Vision–Language Pretraining under Limited Pairing
Robustifying Vision-Language Models via Test-Time Prompt Adaptation
Language-based Trial and Error Falls Behind in the Era of Experience
PACT: Self-Evolving Physical Safety Alignment for Diffusion Policies in Embodied Manipulation
DecepChain: Inducing Deceptive Reasoning in Large Language Models
Prototype-Grounded Concept Models for Verifiable Concept Alignment
Position: Collaborative Agentic AI Needs Interoperability Across Ecosystems
Mixture of Concept Bottleneck Experts
Triadic Dynamics Aware Diffusion Posterior Sampling for Inverse Problems: Optimizing Guidance and Stochasticity Schedules
Offline Reinforcement Learning with Universal Horizon Models
IEC: When Information-Driven Exploration Meets Spectral Consensus via Primal–Dual Reward Regularization in Decentralized Multi-Agent RL
Learning to Decode Against Compositional Hallucination in Video Multimodal Large Language Models
SAEmnesia: Erasing Concepts in Diffusion Models with Supervised Sparse Autoencoders
More Sail than Ballast: Addressing Harmful Knowledge Leakage in the Expansive Reasoning Space of LRMs
MAGIC: A Co-Evolving Attacker–Defender Adversarial Game for Robust LLM Safety
Guidance: Sentence-Level Citation Enforcement via Prefix-Tail Guidance during LLM Decoding
Token-Efficient Change Detection in LLM APIs
Disentangling Intent from Role: Adversarial Self-Play for Persona-Invariant Safety Alignment
A Statistical Framework for Analyzing Specification Resistance to Learnware-Inversion Risks
APEX: Approximate-but-exhaustive search for ultra-large combinatorial synthesis libraries
AICrypto: Evaluating Cryptography Capabilities of Large Language Models
DreamID-Omni: Unified Framework for Controllable Human-Centric Audio-Video Generation
Test-Time Detoxification without Training or Learning Anything
Learning Manifold and Itô Dynamics with Branched Neural Rough Differential Equations
Learning to Watermark in the Latent Space of Generative Models
Masks Can Be Distracting: On Context Comprehension in Diffusion Language Models
S$^3$GNN: Efficient Global Mixing and Local Message Passing for Long-Range Graph Learning
FrontierCS: Evolving Challenges for Evolving Intelligence
Expanding the Chaos: Neural Operator for Stochastic (Partial) Differential Equations
D²Evo: Dual Difficulty-Aware Self-Evolution for Data-Efficient Reinforcement Learning
AnyBand-Diff: A Unified Remote Sensing Image Generation and Band Repair Framework with Spectral Priors
Easier to Judge than to Find: Predicting In-Context Learning Success for Demonstration Selection
Performative Learning Theory
ScaleSim: Serving Large-Scale Multi-Agent Simulation with Invocation Distance-Based Memory Management
Off-Policy Evaluation with Strategic Agents via Local Disclosure
Von Mises-Fisher Mixture Model with Dynamic Shrinkage for Realistic Test-Time Transduction
FUSE: Ensembling Verifiers with Zero Labeled Data
Effective Model Pruning : Measuring the Redundancy of Model Components
In-Context Universal Approximation, Compositional Generalization, and Algorithm Emulation
CausalRAG2: Hierarchical Causal Knowledge Graph Design for RAG
Stein Diffusion Guidance: Training-Free Posterior Correction for Sampling Beyond High-Density Regions
Push, Pop, Parallelize: Stack-Augmented Linear Attention via the Delta Rule
Alignment-Aware Decoding
Multi-scale Explainer for Graph Neural Networks
Unveiling the Entropy Dynamics of Chain-of-Thought Reasoning
Towards A Generative Protein Evolution Machine with DPLM-Evo
Scalable Topology-Preserving Graph Coarsening: Concepts and Algorithms
Universal Approximation with Softmax Attention
Block Rotation is All You Need for MXFP4 Quantization
The Axiomatic Value of Regularization in AI Alignment from Human Preferences
Learning Locally, Revising Globally: Global Reviser for Federated Learning with Noisy Labels
InftyThink+: Effective and Efficient Infinite-Horizon Reasoning via Reinforcement Learning
Convergence of Steepest Descent and Adam under Non-Uniform Smoothness
Scout Before You Attend: Sketch-and-Walk Sparse Attention for Efficient LLM Inference
Light Forcing: Accelerating Autoregressive Video Diffusion via Sparse Attention
Flexible Kernels for Protein Property Prediction
Position Is All You Need: A Free Lunch Token Compression Strategy for MLLM-based Referring Expression Segmentation
AdaHC: Accelerating Multi-Token Prediction with Adaptive Head Chunking with Pipeline Parallelism
Multi-Agent Reinforcement Learning with Submodular Reward
Beyond Point-wise Neural Collapse: A Topology-Aware Hierarchical Classifier for Class-Incremental Learning
What Reward Structure Enables Efficient Sparse-Reward RL? A Proof-of-Concept with Policy-Aware Matrix Completion
Robust-U1: Can MLLMs Self-Recover Corrupted Visual Content for Robust Understanding?
Theory of Continual Learning Against Data Poisoning Attacks
Preference-Modulated Structural Attention for Multi-Objective Combinatorial Optimization
Biologically plausible heavy-tailed connectivity enhances generalizations on cognitive tasks in recurrent neural networks
Position: To Defend Against Cyber Attacks, We Must Teach AI Agents to Hack
Formalizing Learning from Language Feedback with Provable Guarantees
Position: Academic Conferences are Potentially Facing Denominator Gaming Caused by Fully Automated Scientific Agents
Context-Driven Incremental Compression for Multi-Turn Dialogue Generation
Position: Mechanisms for Aggregated Individual Reporting Should be Established for Post-Deployment Evaluation
InfraRL: A Benchmark for Constrained Resource Allocation in Large-Scale Infrastructure Asset Management
SPARD: Defending Harmful Fine-Tuning Attack via Safety Projection with Relevance–Diversity Data Selection
A Hypertoroidal Covering for Perfect Color Equivariance
RELO: Reinforcement Learning to Localize for Visual Object Tracking
Knowing the Unknown: Interpretable Open-World Object Detection via Concept Decomposition Model
Position: We Need Large Language Models Optimized For Our Well-Being
Distributionally Robust Causal Abstractions
Understanding Private Learning From Feature Perspective
Dustin: Draft-Augmented Sparse Verification for Efficient Long-Context Generation with Speculative Decoding
Benign Overfitting in Adversarial Training for Vision Transformers
Understanding Generalization and Forgetting in In-Context Continual Learning
Contrastive Representation Regularization for Vision-Language-Action Models
GOCM: Single-Step Graph Outlier Synthesis via Origin Consistency Model
Do Activation Verbalization Methods Convey Privileged Information?
MVP-LAM: Learning Action-Centric Latent Action via Cross-Viewpoint Reconstruction
Transformers with RL or SFT Provably Learn Sparse Boolean Functions, But Differently
CodeMamba: Shifting from Target Semantics to Self-Supervised Background Manifold Learning for Singularity Detection in Infrared Sequences
Beyond Policy Training: Recursive Solution Search from Unannotated Videos
Learning Rate Scaling across LoRA Ranks and Transfer to Full Finetuning
Geometry-Aware Dataset Condensation for Diffusion Model Training
RN-D: Discretized Categorical Actors for On-Policy Reinforcement Learning
Transformers Efficiently Perform In-Context Logistic Regression via Normalized Gradient Descent
Adaptive Contracts for Cost-Effective AI Delegation
Learning Gaussian Mixture-distributed Prototypes for 3D Scene Graph Generation from RGB-D Sequences
Think Twice Before You Act: Protecting LLM Agents Against Tool Description Poisoning via Isolated Planning
Diversity-Preserved Distribution Matching Distillation for Fast Visual Synthesis
Pair2Scene: Learning Local Object Relations for Procedural Scene Generation
Fast KV Compaction via Attention Matching
Unified Multimodal Autoregressive Modeling with Shared Context—Visual Tokenizer is Key to Unification
Do LLMs Signal When They’re Right? Evidence from Neuron Agreement
MAS-Orchestra: Understanding and Improving Multi-Agent Reasoning Through Holistic Orchestration and Controlled Benchmarks
Semi-LAR: Semi-supervised Contrastive Learning with Linear Attention for Removal of Nighttime Flares
Self-Supervised Flow Matching for Scalable Multi-Modal Synthesis
Q-DiT4SR: Exploration of Detail-Preserving Diffusion Transformer Quantization for Real-World Image Super-Resolution
Position: Age Estimation Models Do Not Process Biometric Data
Reward Redistribution for CVaR MDPs using a Bellman Operator on L-infinity
Learning the Neighborhood: Contrast-Free Multimodal Self-Supervised Molecular Graph Pretraining
Learning with Admissibility: Robust Fuzzy Hashing for Cross-Modal Retrieval with Noisy Labels
VideoBrain: Learning Adaptive Frame Sampling for Long Video Understanding
Strat-Reasoner: Reinforcing Strategic Reasoning of LLMs in Multi-Agent Games
Necessary Conditions for Compositional Generalization of Embedding Models
How can embedding models bind concepts?
RLSF-V: Mitigating Hallucinations in MLLMs via Fuzzy Semantic Self-Feedback
OcclusionFormer: Arranging Z-Order for Layout-Grounded Image Generation
Dropout Universality: Scaling Laws and Optimal Scheduling at the Edge-of-Chaos
OServe: Accelerating LLM Serving via Spatial-Temporal Workload Orchestration
AReaL-DTA: Dynamic Tree Attention for Efficient Reinforcement Learning of Large Language Models
DITING: A Weak Degradation Listener for Battery Lifetime Early Prediction
Adaptive Policy Backbone via Shared Network
Position: The Term “Machine Unlearning” Is Overused in LLMs
DOUBT: Decoupled Object-level Understanding and Bridging via vMF-based Trustworthiness for Hallucination Detection in MLLMs
Posterior Mismatch Matters: Adversarial Training for Long-Tailed Robustness
Multimodal Nested Learning for Decoupled and Coordinated Optimization
Characterizing the Effect of Noise in Language Generation in the Limit
Bad Seeing or Bad Thinking? Rewarding Perception for Multimodal Reasoning
StormInsight: Hierarchical Environmental Forcing and Vertical Coupling for Weather System Evolution
FlowNar: Scalable Streaming Narration for Long-Form Videos
Towards Hierarchy–Uniformity Equilibrium: Recovering Semantic Depth in Hypergraph Contrastive Learning
MAS-Architect: Declarative Multi-Agent System Design via Separation of Concerns
What Linear Probes Miss: Multi-View Probing for Weight-Space Learning
TPGDiff : Hierarchical Triple-Prior Guided Diffusion for Image Restoration
Foundation VAE for CT Reconstruction, Augmentation, and Generation
STT-LLM: Structural-Temporal Tokenization for Adapting LLMs to Longitudinal Clinical Profiles
Structured Diffusion Bridges: Inductive Bias for Denoising Diffusion Bridges
LangPrecip: Language-Aware Multimodal Precipitation Nowcasting
DecomPose: Disentangling Cross-Category Optimization Contention for Category-Level 6D Object Pose Estimation
Beyond Unidirectional Bias: Reciprocal Perspective Calibration in Scene Graph Generation
HieraScaffold: Learning Compact Hierarchical Representations for Scalable 4D LiDAR Generation
GeoLoom: High-quality Geometric Diagram Generation from Textual Input
Overcoming PINNs Failure Modes In High Dimension With Low-Rank Fourier Sum
Adaptive Coding Emerges in Stabilized Supralinear Networks Trained with Local Plasticity
StitchCUDA: An Automated Multi-Agents End-to-End GPU Programing Framework with Rubric-based Agentic Reinforcement Learning
Speculative Coupled Decoding for Training-Free Lossless Acceleration of Autoregressive Visual Generation
GO-PRE: Goal-Oriented Next-Best-View Selection via Predictive Rendering Entropy for Active 3D Reconstruction
FUSE: Frequency-domain Unification and Spectral Energy Alignment for Multi-modal Object Re-Identification
MC-HNN: Learning Latent Structural Semantics and High-Rank Representations for Hypergraph Neural Networks
In-Context Learning Is Provably Bayesian Inference: A Generalization Theory for Meta-Learning
Welfare-Optimal Classification with Accuracy Auctions
Normalization Equivariance for Arbitrary Backbones, with Application to Image Denoising
From Extrinsic to Intrinsic: Geodesic-Guided Representation Learning for 3D Geometric Data
MedCRP-CL: Continual Medical Image Segmentation via Bayesian Nonparametric Semantic Modality Discovery
Inference Time Optimization with Confidence Dynamics
Unifying Masked Diffusion Models with Various Generation Orders and Beyond
HumanLM: Simulating Users with State Alignment Beats Response Imitation
AdaSCALE: Adaptive Scaling for OOD Detection
Geometry-Preserving Orthonormal Initialization for Low-Rank Adaptation in RLVR
Sonar-TS: Search-Then-Verify Natural Language Querying for Time Series Databases
UOTIP: Unbalanced Optimal Transport Map for Unpaired Inverse Problems
TokenDrop: Token-Level Importance-Aware Backward Propagation Skipping for Efficient LLM Fine-Tuning
SEER: Transformer-based Robust Time Series Forecasting via Automated Patch Enhancement and Replacement
Position: Anthropomorphic Misalignment Research Needs Stronger Evidence
Universal Algorithm-Implicit Learning
GICDM: Mitigating Hubness for Reliable Distance-Based Generative Model Evaluation
TriForces: Augmenting Atomistic GNNs for Transferable Representations
ToMoE: Converting Dense Large Language Models to Mixture-of-Experts through Dynamic Structural Pruning
Multi-Task Bayesian In-Context Learning
Rational Neural Networks have Expressivity Advantages
One Coin Has Two Sides: Single Poistive Multi Label Learning from Salient Annotations
Ask Less, See More: Communication-Conditioned Token Pruning for Vehicle-to-Vehicle Cooperative Autonomous Driving with Multimodal Large Language Models
Alignment between Brains and AI: Evidence for Convergent Evolution across Modalities, Scales and Training Trajectories
Rectified LpJEPA: Joint-Embedding Predictive Architectures with Sparse and Maximum-Entropy Representations
Position: The Systemic Lack of Agency in Visual Reasoning
Generalized Boundary FDR Control under Arbitrary Dependence: An Approach on Closure Principle
Trees to Flows and Back: Unifying Decision Trees and Diffusion Models
Image-to-Brain Signal Generation for Visual Prosthesis with CLIP Guided Multimodal Diffusion Models
Steering at the Source: Style Modulation Heads for Robust Persona Control
Learning Multi-Scale Hypergraph for High-Order Brain Connectivity Analysis
Recognize Your Orchestrator: An Entropy Dynamics Perspective for LLM Multi-Agent Systems
Frequency Matching in Spiking Neural Networks for mmWave Sensing
Multimodal Fusion via Self-Consistent Task-Gradient Fields
Seeing is Understanding: Unlocking Causal Attention into Modality-Mutual Attention for Multimodal LLMs
Abstraction Induces the Brain Alignment of Language and Speech Models
Geometry-based Schrödinger Bridges for Trustworthy Multimodal Fusion
Stochastic Lifting for Generating Trajectories of Stochastic Physical Systems
Modeling Long-Tail Relations in the Operating Room via In-Context Multimodal Learning
Adaptive Testing for LLM Evaluation: A Psychometric Alternative to Static Benchmarks
Noise-corrected GRPO: From Noisy Rewards to Unbiased Gradients
Exploiting weight-space symmetries for approximating curvature
Hierarchical Goal Abstractions via Learned Subset Relations
Adaptive DNA Sequence Modeling via Synergistic Plasticity Units
LassoFlexNet: a Flexible Neural Architecture for Tabular Data
Discriminative Mixture-of-Experts on Graphs with Reliable Expert Fusion
MICE-Bench: A Challenging and Comprehensive Benchmark for Multi-Reference Image Creation and Editing
Geometry-Guided Modeling of Foundation Features Enables Generalizable Object Shape Deformation Learning
Cross-Embodiment Robot Foundation World Models with Latent Actions
Terminal Dimension Reduction for Time Series with Applications
Intrinsic Task Symmetry Drives Generalization in Algorithmic Tasks
Verbalized Bayesian Persuasion
Scalable and Stable Estimation of Amari $\alpha$-Divergence using Random Fourier Features
CofactGVR: Counterfactual Intervention for Grounded Visual Reasoning
Should I Have Expressed a Different Intent? Counterfactual Generation for LLM-Based Autonomous Control
Event2Vec: Processing neuromorphic events directly by representations in vector space
Gram2Token: Enabling Run-time GPU-Native Grammar-Constrained Decoding for LLMs
RAMAC: Multimodal Risk-Aware Offline Reinforcement Learning and the Role of Behavior Regularization
STARCaster: Spatio-Temporal AutoRegressive Video Diffusion for Identity- and View-Aware Talking Portraits
ProactiveLLM: Learning Active Interaction for Streaming Large Language Models
Task-Aware Mechanism: Hybrid MoE Vision Tower Towards Holistic Video Understanding
Revealing Scaling Paradox in Large-scale Time Series Models: Implications for More Efficient and Accurate Forecasting
GFFMERGE: Efficient Merging of Graph Neural Force Fields and Beyond
Efficient Stochastic Optimisation via Sequential Monte Carlo
Scalable Simulation-Based Model Inference with Test-Time Complexity Control
Learning Self-Correction in Vision–Language Models via Rollout Augmentation
PRISM: Distribution-free Adaptive Computation of Matrix Functions for Accelerating Neural Network Training
AffIn-Space: Learning Affine-Invariant Representations for 3D Spatial Understanding with MLLMs
What Makes Synthetic Data Effective in Image Segmentation
CVSearch: Empowering Multimodal LLMs with Cognitive Visual Search for High-Resolution Image Perception
ProSAR: Prototype-Guided Semantic Augmentation and Refinement for Time Series Contrastive Learning
NetDiff: Graph Diffusion with Improved Global Capabilities to Generate and Update Mobile Network Topologies
DISCO: Mitigating Bias in Deep Learning with Conditional Distance Correlation
FusionCell: Cross-Attentive Fusion of Layout Geometry and Netlist Topology for Standard-Cell Performance Prediction
Rank-Learner: Orthogonal Ranking of Treatment Effects
AlignVid: Taming Visual Dominance via Training-Free Attention Modulation in Text-guided Image-to-Video Generation
Frictional Q-Learning
StructMAR: Structure-Aware Masked Autoregression for Explicit Layout Alignment in Text-to-Image Generation
The Assistant Axis: Situating and Stabilizing the Default Persona of Language Models
Adversarially Robust Control of Conditional Value-at-Risk via Rockafellar-Uryasev Conformal Inference
Reward-free Alignment for Conflicting Objectives
Position: Federated Learning is a Lens towards a Democratized Future for the Scaling Law Era
How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs
DiffuMamba: High-Throughput Diffusion LMs with Mamba Backbone
SPADA: A Verifiable Test-Driven Agent for Controllable Parametric CAD Assembly Generation
Position: Epistemic uncertainty estimation methods are fundamentally incomplete
SVL: Empowering Spiking Neural Networks for Efficient 3D Open-World Understanding
ReQAT: Achieving Full-Precision Reasoning Accuracy with 4-bit Floating-Point Quantization-Aware Training
HInT: Hypergraph Infusion at the Structural Layers Improves Table Understanding
Olivia: Harmonizing Time Series Foundation Models with Power Spectral Density
DV-World: Benchmarking Data Visualization Agents in Real-World Scenarios
d$^2$p: Structured Soft Attention Is All You Need
Refined Analysis of Entropy-Regularized Actor-Critic
Efficient and Unbiased Sampling from Boltzmann Distributions via Variance-Tuned Diffusion Models
Benchmarking World-Model Learning with Environment-Level Queries
Improving Zero-Shot Offline RL via Behavioral Task Sampling
Beyond Theorem Proving: Formulation, Framework and Benchmark for Formal Problem-Solving
Expected Returns and Policy Inconsistency-Aware Offline Federated Deep Reinforcement Learning
Continuous Diffusion Models Can Obey Formal Syntax
Offline Reinforcement Learning of High-Quality Behaviors Under Robust Style Alignment
Position: Invisible Tokens, Visible Bills: The Urgent Need to Audit Hidden Operations in Opaque LLM Services
Flatness-Aware Stochastic Gradient Langevin Dynamics
Interpreting Physics in Video World Models
Position: The Inevitable Transition to Machine Learning in Quantum Chemistry
At the Edge of Understanding: Sparse Autoencoders Trace The Limits of Transformer Generalization
Position: Reasoning After Perception Means Reasoning Without Vision
The Pareto-optimal Trade-off between Regret and Statistical Inference in Linear Stochastic Bandits under Safety Constraints
Efficient Neural Controlled Differential Equations via Attentive Kernel Smoothing
CSPO: Constraint-Sensitive Policy Optimization for Safe Reinforcement Learning
BESPOKE: Benchmark for Search-Augmented Large Language Model Personalization via Diagnostic Feedback
RED-HDP-HMM: Observation-Dependent Durations for Bayesian Nonparametric Sequential Models
The Lie We Tell: Correcting the Euclidean Fallacy in Vision Language Action Policies via Score Matching on Tangent Space
Geometry-Guided Generative Representation for Functional Brain Graphs
A Flat Vocabulary or a Rich Hierarchy? Re-introducing Intrinsic Structure Transforms the Autoregressive Image Generation
Understanding LoRA as Knowledge Memory: An Empirical Analysis
CoRe: Combined Rewards with Vision-Language Model Feedback for Preference-Aligned Reinforcement Learning
Adversarial Robustness of Implicit Neural Representation-Based Classifiers
Sharp Inequalities between Total Variation and Hellinger Distances for Gaussian Mixtures
REAR: Test-time Preference Realignment through Reward Decomposition
Neural Minimum Weight Perfect Matching for Quantum Error Codes
Unitary Convolutions for Message-passing and Positional Encodings on Directed Graphs
Benchmarking and Enhancing VLM for Compressed Image Understanding
Decoupling The "What" and "Where" With Polar Coordinate Positional Embedding
From Parameters to Data: A Task-Parameter-Guided Fine-Tuning Pipeline for Efficient LLM Alignment
MIST: Moment-Aligned Invariant Stability Transform for Robust Flow Matching
Time-PEFT: Temporal and Multichannel Complexity-Based Fine-Tuning for Time-Series Foundation Models
LoSA: Locality Aware Sparse Attention in Diffusion Language Models
Residual Context Diffusion Language Models
Autoregressive Image Generation with Masked Bit Modeling
Accelerating Q-learning through Efficient Value-sharing across Actions
Mitigating Perceptual Judgment Bias in Multimodal LLM-as-a-Judge via Perceptual Perturbation and Reward Modeling
Prioritized Model Experience Replay
Stable Deep Reinforcement Learning via Isotropic Gaussian Representations
SelfJudge: Faster Speculative Decoding via Self-Supervised Judge Verification
Learning Adaptive Perturbation-Conditioned Contexts for Robust Transcriptional Response Prediction
How to Guide Your Flow: Few-Step Alignment via Flow Map Reward Guidance
SeisMark: A Large-Scale Open Benchmark for Robust 3D Seismic Fault Detection
Biased Generalization in Diffusion Models
CONTINUUM: Restoring the Contiguous Tensor Abstraction Efficiently for Dynamic AI Workloads via Hardware Virtualization
Differentiable Conformal Training for LLM Reasoning Factuality
Probabilistically-routed Bayesian Additive Spanning Trees for Learning on Constrained Domains
Position: Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning
Decision Transformers As Zero-Shot Learners via Text-Behavior Alignment
KIStego: Key-Independent Secure Image Distribution via Bipartite Structural Invariants
NonZero: Interaction-Guided Exploration for Multi-Agent Monte Carlo Tree Search
Beyond Majority Voting: Self-Reflective Test-Time Reinforcement Learning for LLM Reasoning
Robust Self-reflective Hashing for Cross-modal Retrieval with Noisy Label
Cycle-of-Science: Reliable Reasoning through Counterfactual Verification for Agent Decision Making
DiasR: Dual-Modal Identity-Anchored Sparse Routing for Efficient Multi-Subject Video Generation
Distributionally Robust Markov Games with Average Reward
Recurrent Structural Policy Gradient for Partially Observable Mean Field Games
Taylor-Gaussians-Flow: Towards Non-uniform Motion for Novel View Synthesis from Monocular Video
Discovering Implicit Large Language Model Alignment Objectives
AtelierEval: Agentic Evaluation of Humans & LLMs as Text-to-Image Prompters
Continual Learning through Control Minimization
VLA-Arena: An Open-Source Framework for Benchmarking Vision-Language-Action Models
Return-Critic: Bridging Goal Discrepancy for Efficient Visual Reinforcement Learning
Hybrid Reinforcement Learning in Adversarial Markov Decision Processes
CSG: Cognitive Structure Generation for Intelligent Education
DeepAnalyze: Agentic Large Language Models for Autonomous Data Science
FLIP2: Expanding Protein Fitness Landscape Benchmarks for Real-World Machine Learning Applications
CoDA-Bench: Can Code Agents Handle Data-Intensive Tasks?
Low-cost Full Fine-tuning: Learning What to Update for LLMs
HyperPotter: Spell the Charm of High-Order Interactions in Audio Deepfake Detection
Scalable GANs with Transformers
Position: Hippocampal Explicit Memory Is a Cornerstone to Human-Level AI
MADE: Benchmark Environments for Closed-Loop Materials Discovery
Phase-Aware Mixture of Experts for Agentic Reinforcement Learning
Benchmarking Reward Hack Detection in Code Environments via Contrastive Analysis
BLISS: A Lightweight Bilevel Influence Scoring Method for Data Selection in Language Model Pretraining
When Do Hallucinations Arise? A Graph Perspective on the Evolution of Path Reuse and Path Compression
Beyond Attention Imbalance: Mitigating Hallucinations via Spectral Surgery
LOCA-bench: Benchmarking Language Agents Under Controllable and Extreme Context Growth
Embedding Trust: Semantic Isotropy Predicts Nonfactuality in Long-Form Text Generation
N2M: Bridging Navigation and Manipulation by Learning Pose Preference from Rollout
Rh-3DGS: Robust Open-Vocabulary Scene Understanding via Riemannian Huber Distillation and Manifold-Aware Sampling
When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems
Modelling Attention with Aitchison Geometry: Token Distinguishability and Temperature Scaling
HyPOLE: Hyperproperty-Guided Multi-Agent Reinforcement Learning under Partial Observation
Action Manifold Smoothing: A Lipschitz Pathway Perspective on High-Dimensional Reinforcement Learning
Don't Reinvent the Wheel, Just Realign the Spokes: Resource-Efficient Federated Fine-Tuning via Rank-Wise Expert Assembly
A Random Matrix Theory of Masked Self-Supervised Learning
Golden Goose: A Simple Trick to Synthesize Unlimited RLVR Tasks from Unverifiable Internet Text
NITP: Next Implicit Token Prediction for LLM Pre-training
Cascaded Flow Matching for Heterogeneous Tabular Data with Mixed-Type Features
Accuracy and Normalized Accuracy under Length Bias: Analysis, Guidelines, and a Bayesian Alternative
Understanding MARS: When Scaling Momentum Provably Helps
Nonparametric Distribution Regression Re-calibration
From Muon to Gluon: Bridging Theory and Practice of LMO-based Optimizers for LLMs
The Geometric Reasoner: Manifold-Informed Latent Foresight Search for Long-Context Reasoning
Weight-sparse transformers have interpretable circuits
Context Tuning for In-Context Optimization
SparseOpt: Addressing Normalization-induced Gradient Skew in Sparse Training
$\texttt{MetaDistill}$: Unlocking the Performance Ceiling for Pretrained Optimizers
Thinking with Geometry: Active Geometry Integration for Spatial Reasoning
ScaleErasure: Inference-Time Minimal Intervention for Precise Concept Erasure in Next-Scale Autoregressive Image Generation
Reward Auditor: Inference on Reward Modeling Suitability in Real-World Perturbed Scenarios
CIRBench: Evaluating Large Language Models as LLVM IR Optimizers
Balanced LoRA: Removing Parameter Invariance to Accelerate Convergence
WestWorld: A Knowledge-Encoded Scalable Trajectory World Model for Diverse Robotic Systems
Anatomy of Massive Activations and Attention Sinks
Certain Head, Uncertain Tail: Expert-Sample for Test-Time Scaling in Fine-Grained MoE
Optimal Regret for Policy Optimization in Contextual Bandits
Singularity-aware Optimization via Randomized Geometric Probing: Towards Stable Non-smooth Optimization
Reasoning-VLA: An Efficient and Spatial-Guided General Vision-Language-Action Reasoning Model for Autonomous Driving
STD-Former: Image-Conditioned Texture Dictionary Encoding with Sparse Topological Supervision for Texture Recognition
Distributed Direct Preference Optimization
Difference-Aware Decision Learning for Multimodal Image Fusion
Periodic Bayesian Flow Networks with Additive Accuracy
An Asymmetric Latent Factorization-of-Tensors Model for Relation Analysis
Linguistic Properties and Model Scale in Brain Encoding: From Small to Compressed Language Models
Scale-Aware Domain Harmonization for Domain Adaptation Person Search
MACD: Model-Aware Contrastive Decoding via Counterfactual Data for Video-LLMs
Characterizing Agents in Production
Scalable Option Learning in High-Throughput Environments
Modular Pretraining Enables Access Control
Discretely-Refined Multi-view Clustering via Aligned Anchor Learning
Neural Vector Lyapunov–Razumikhin Certificates for Delayed Interconnected Systems
Hierarchical Decision Making with Structured Policies: A Principled Design via Inverse Optimization
3D-RFT: Reinforcement Fine-Tuning for Video-based 3D Scene Understanding
TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization
FLAC: Maximum Entropy RL via Kinetic Energy Regularized Bridge Matching
Toward Subspace-Perturbed Trajectory-Aware Backdoor Attacks in Deep Reinforcement Learning
Stable Velocity: A Variance Perspective on Flow Matching
Absorbing Quantization Error by Deformable Noise Scheduler for Diffusion Models
Visual Para-Thinker: Divide-and-Conquer Reasoning for Visual Comprehension
BPDQ: Bit-Plane Decomposition Quantization on a Variable Grid for Large Language Models
OmniSIFT: Modality-Asymmetric Token Compression for Efficient Omni-modal Large Language Models
ACON: Optimizing Context Compression for Long-horizon LLM Agents
The Geometry of Reasoning: Self-Evaluation via Layerwise Trajectory Evolution
RLCracker: Evaluating the Worst-Case Vulnerability of LLM Watermarks with Adaptive RL Attacks
Deep Single-Index Fréchet Regression
Symmetries in language statistics shape the geometry of model representations
Interpreting Genomic Language Models using Sparse Autoencoders
GameDevBench: Evaluating Agentic Capabilities Through Game Development
GEM: Geometric Entropy Mixing for Optimal LLM Data Curation
DyLLM: Efficient Diffusion LLM Inference via Saliency-based Token Selection and Partial Attention
Time-Conditioned Foreseeing: An EHR-Specific Foundation Model for Irregular Dynamics and Calendrical Time
Beyond Binary: Continuous State Optimization with Graph-Structured Objectives
Realizable Bayes-Consistency for General Metric Losses
Probabilistic Modeling of Latent Agentic Substructures in Deep Neural Networks
A Refined Generalization Analysis for Extreme Multi-class Supervised Contrastive Representation Learning
Semantic Router: On the Feasibility of Hijacking MLLMs via a Single Adversarial Perturbation
Provably Data-driven Multiple Hyper-parameter Tuning with Structured Loss Function
Structure-aware Granular-Ball based Information Bottleneck for Multi-modal Clustering
WMVLM: Evaluating Diffusion Model Image Watermarking via Vision-Language Models
Context Forcing: Consistent Autoregressive Video Generation with Long Context
Experience-Evolving Multi-Turn Tool-Use Agent with Hybrid Episodic–Procedural Memory
Moment Matching Q-Learning
Harmful Overfitting in Sobolev Spaces
Gated Relational Alignment via Confidence-based Distillation for Efficient VLMs
Fast Estimation for Forest Matrix of Signed Graphs
Toward Calibrated Mixture-of-Experts Under Distribution Shift
SpikeCLR: Self-Supervised Contrastive Learning for Visual Representations with Spiking Neural Networks
Hyperparameter Transfer with Mixture-of-Expert Layers
Conformal Policy Control
Explaining Data Mixing Scaling Laws
High-Dimensional Learning Dynamics of Quantized Models with Straight-Through Estimator
WeDLM: Reconciling Diffusion Language Models with Standard Causal Attention for Fast Inference
Optimizing Agentic Reasoning with Retrieval via Synthetic Semantic Information Gain Reward
Negative Sampling From the Ground Up: A Redesign for Recommendation
FedHera: Towards Drift-Resilient Federated Fine-tuning with Heterogeneous Resources
BM^2: Coupled Schrödinger Bridge Matching
Multi-Accurate CATE is Robust to Unknown Covariate Shifts
Depth-Progressive Monotonic Learning without Global Backpropagation
TimeChat-Captioner: Scripting Multi-Scene Videos with Time-Aware and Structural Audio-Visual Captions
Linear Causal Representation Learning by Topological Ordering, Pruning, and Disentanglement
Probability-Entropy Calibration: An Elastic Indicator for Adaptive Fine-tuning
Rethinking the Flow-based Gradual Domain Adaptation: A Semi-Dual Optimal Transport Perspective
Mitigating Surgical Data Imbalance with Dual-Prediction Video Diffusion Model
SkillTrojan: Backdoor Attacks on Skill-Based Agent Systems
TRIP-Bench: A Benchmark for Long-Horizon Interactive Agents in Real-World Scenarios
Transfer Learning in High-dimensional Ising Models
Vision-DeepResearch: Incentivizing DeepResearch Capability in Multimodal Large Language Models
OMAC: A Holistic Optimization Framework for LLM-Based Multi-Agent Collaboration
D-ARL: A Distribution-Matched Asynchronous Reinforcement Learning Framework for Language Reasoning
Adversarial Latent Embedding Repair for LLM Continual Learning
On the Sharp Input-Output Analysis of Nonlinear Systems under Adversarial Attacks
V1: Unifying Generation and Self-Verification for Parallel Reasoners
Distillation Models are Good Samplers for Diffusion Reinforcement Learning
Prediction-Powered Risk Monitoring of Deployed Models for Detecting Harmful Distribution Shifts
Universal Skeleton Understanding via Differentiable Rendering and MLLMs
Models Under SCOPE: Scalable and Controllable Routing via Pre-hoc Reasoning
How to Price Data: A Market Equilibrium Based Approach
Causal Dependency-Aware Unsupervised Routing for Large Reasoning Models
DeepImageSearch: Benchmarking Multimodal Agents for Context-Aware Image Retrieval in Visual Histories
Self-Captioning Multimodal Interaction Tuning: Amplifying Exploitable Redundancies for Robust Vision Language Models
Diversity-aware Weight Perturbation Promotes Robust Adaptation
Learning the Interaction Prior for Protein-Protein Interaction Prediction: A Model-Agnostic Approach
Partial Identification of Policy Values under Network Interference
Towards Fine-Grained Robustness: Attention-Guided Test-Time Prompt Tuning for Vision-Language Models
SegPVSG: Panoptic Video Scene Graph Generation via Temporal Focusing and Generative Augmentation
REST: Diffusion-based Real-time End-to-end Streaming Talking Head Generation via ID-Context Caching and Asynchronous Streaming Distillation
Context-free Recognition with Transformers
FOCUS: DLLMs Know How to Tame Their Compute Bound
OptMaster: A DAG-Based Framework for Formulation and Heuristic Discovery in Optimization
Learning the Minimum Action Distance
DAG-MoE: From Simple Mixture to Structural Aggregation in Mixture-of-Experts
Feedback Control for Multi-Objective Graph Self-Supervision
VidLaDA: Bidirectional Diffusion Large Language Models for Efficient Video Understanding
xKV: Cross-Layer KV-Cache Compression via Aligned Singular Vector Extraction
How RLHF Amplifies Sycophancy
DAISI: Data Assimilation with Inverse Sampling using Stochastic Interpolants
Outcome-Aware Spectral Feature Learning for Instrumental Variable Regression
Verbalized Sampling: How to Mitigate Mode Collapse and Unlock LLM Diversity
Meta Context Engineering via Agentic Skill Evolution
A Tale of Two Graphs: Separating Knowledge Exploration from Outline Structure for Open-Ended Deep Research
Persistent Semantic Entities in Tool-Augmented LLM Systems
Toward Scalable and Valid Conditional Independence Testing with Spectral Representations
Position: Hallucinations Undermine Trust; Metacognition is a Way Forward
Light Up Your Face: A Physically Consistent Dataset and Diffusion Model for Face Fill-Light Enhancement
Zeroth-Order Forward-Only SNN Training Inspiring Neuromorphic On-Chip Learning
Federated Causal Inference on Multi-Site Observational Data via Propensity Score Aggregation
Geometry-Aware Decoding with Wasserstein-Regularized Truncation and Mass Penalties for Large Language Models
Multi-View Causal Discovery without Non-Gaussianity: Identifiability and Algorithms
Geometry-Aware Probabilistic Circuits via Voronoi Tessellations
Coupled Trigger Optimization and Vulnerable Parameter Alignment for Persistent Backdoor Attacks on Federated Learning
Position: Beyond Reasoning Zombies — AI Reasoning Requires Process Validity
Optimization, Generalization and Differential Privacy Bounds for Gradient Descent on Kolmogorov–Arnold Networks
Prefix-Cache-Aware Data Reordering for LLM-Augmented Database Analytics
Treatment Responder Classification with Abstention
Agentic Model Predictive Questioning Control in Visual Design
SpecForge: A Flexible and Efficient Open-Source Training Framework for Speculative Decoding
Physics-Informed Residual Flows
Heavy-tailed Physics-Informed Neural Networks
AutoMat: Physics-Guided Agentic Reasoning for Solving Ill-Posed Inverse Microscopy Problems
Rex: A Family of Reversible Exponential (Stochastic) Runge-Kutta Solvers
Skipping the Zeros in Diffusion Models for Sparse Data Generation
Formally Exploring Visual Anomaly Detection Evaluation Metrics
VenusBench-Mobile: A Challenging and User-Centric Benchmark for Mobile GUI Agents with Capability Diagnostics
Bridging the Gap Between Average and Discounted TD Learning
The Obfuscation Atlas: Mapping Where Honesty Emerges in RLVR with Deception Probes
EmWorld: Emotion World Model with Latent State Evolution for Scenario-Incremental Dynamic Facial Expression Recognition
World-Model Inspired Emotion-aware Token Refinement for Training-Free Multimodal Emotion Recognition
Breaking the Computational Barrier: Provably Efficient Actor–Critic for Low-Rank MDPs
ConvexBench: Can LLMs Recognize Convex Functions?
See the Emotion: A Facial Emoji Proxy Modeling for EEG Emotion Recognition
Even Faster Kernel Matrix Linear Algebra via Density Estimation
Regularized Offline Policy Optimization with Posterior Hybrid Bayesian Belief
dTRPO : Trajectory Reduction in Policy Optimization of Diffusion Large Language Models
NeuronCtrl: Geometry-Aware Safe Closed-Loop Generative Control for Neuronal Microenvironment Dynamics
Surgery: Mitigating Harmful Fine-Tuning for Large Language Models via Attention Sink
GaussTrace: Provenance Analysis of 3D Gaussian Splatting Models with Evidence-based LLM Reasoning
SWE-rebench V2: Language-Agnostic SWE Task Collection at Scale
KernelCraft: Benchmarking for Agentic Close-to-Metal Kernel Generation on Emerging Hardware
Rewiring Experts on the Fly: Continuous Rerouting for Better Online Adaptation in Mixture-of-Expert Models
PACER: Acyclic Causal Discovery from Large-scale Interventional Data
A Direct Second-Order Method for Solving Two-Player Zero-Sum Games
Backjump-on-Graph: Empowering Large Language Models with Reinforced Retrospective Exploration for Agentic Knowledge Graph Reasoning
Rethinking Thinking Tokens: LLMs as Improvement Operators
FairSSL: Fair Multimodal Self-Supervised Learning
Efficient Learning of Deep State Space Models via Importance Smoothing
Position: Peer Review in ML/AI Conferences Should Separate Publication from Presentation and Offer Non-Anonymous Review Tracks
TGPO: Efficient Policy Optimization through Sequence Anchor and Information Gating
A Bi-metric Framework for Efficient Nearest Neighbor Search
Simple Denoising Diffusion Language Models
Towards Theoretical Understanding of Transformer Test-Time Computing: Investigation on In-Context Linear Regression
Foundation Inference Models for Ordinary Differential Equations
FocalPolicy: Frequency-Optimized Chunking and Locally Anchored Flow Matching for Coherent Visuomotor Policy
DLM-Scope: Mechanistic Interpretability of Diffusion Language Models via Sparse Autoencoders
Inverse Entropic Optimal Transport Solves Semi-supervised Learning via Data Likelihood Maximization
VideoTrace-R1: Long Video-based Retrieval-Augmented Generation via Reinforcement Learning
PyPop7: A Pure-Python Library for Population-Based Black-Box Optimization
Position: Zeroth-Order Optimization in Deep Learning Is Underexplored, Not Underpowered
Discrete Survival Knowledge Distillation for Competing Risks Analysis
On Training Large Language Models for Long-Horizon Tasks: An Empirical Study of Horizon Length
GKD-Recruiter: Jointly Modeling Social and Task Heterogeneity for Spatial Crowdsourcing via Graph Knowledge Distillation
Position: Artificial Intelligence Needs Meta Intelligence - the Case for Metacognitive AI
Dynamics Reveals Structure: Challenging the Linear Propagation Assumption
Split Personality Training: Revealing Latent Knowledge Through Alternate Personalities
Telescope: Improving Zero Shot Detection of LLM Generated Content By Measuring Token Repetition Probability
Turbo4DGen: Ultra-Fast Acceleration for 4D Generation
GeoSense: Internalizing Geometric Necessity Perception for Multimodal Reasoning
PhysHanDI: Physics-Based Reconstruction of Hand-Deformable Object Interactions
Position: Quantum Kernel Machines Should Move Beyond Scalar-Valued Kernels to Realize Their Potential
Logit Distance Bounds Representational Similarity
Local MAP Sampling for Diffusion Models
SURGE: Approximation and Training Free Particle Filter for Diffusion Surrogate
From Parameters to Feature Space: Task Arithmetic for Backdoor Mitigation in Model Merging
Time Series Reasoning via Process-Verifiable Thinking Data Synthesis and Scheduling for Tailored LLM Reasoning
Translation Heads: Disentangling meaning from language in LLM-based machine translation
Position: Significant impact of numerical precision in scientific machine learning
MiniAppBench: Evaluating the Shift from Text to Interactive HTML Responses in LLM-Powered Assistants
Bridging RGB and RAW: Single-step Deterministic Flow with Homogeneous Representation Alignment
Learning Multi-Agent Coordination via Sheaf-ADMM
ScalingAR: Scaling Confidence for Autoregressive Image Generation
Geometric Flow Grounding: A Unified Manifold Decoupling Framework for Dynamics Discovery and Verification
Budget-Constrained Step-Level Diffusion Caching
SCORE: A Unified Framework for Overshoot Refund in Online FDR Control
Conformal Reliability: A New Evaluation Metric for Conditional Generation
CAPTCHA Solving for Native GUI Agents: Automated Reasoning-Action Data Generation and Self-Corrective Training
BiSSL: Enhancing the Alignment Between Self-Supervised Pretraining and Downstream Fine-Tuning via Bilevel Optimization
GoodDiffusion: Proactive Copyright Protection for Diffusion Generative Models via Learnable Sample-specific Signatures
Can Computational Reducibility Lead to Transferable Models for Graph Combinatorial Optimization?
Accurate Large-sample Uncertainty Quantification using Stochastic Gradient Markov Chain Monte Carlo
HONet: Data-Efficient Learning for Exact Cover Tasks via Hypergraph Optimization
Position: Evaluation of ML Resource Utilization Requires Model Life Cycle Assessment
Position: Enabling Fair Revenue Sharing for Data Providers in GenAI Systems
Interaction-Breaking Adversarial Learning Framework for Robust Multi-Agent Reinforcement Learning
OmniFit: Bridging Modalities via Layer-Adaptive Token Compression for Omnimodal Large Language Models
Statistical Impossibility and Possibility of Aligning LLMs with Human Preferences: From Condorcet Paradox to Nash Equilibrium
Similarity Is Not Logic: Factored Inference for Dual-Encoder Vision-Language Models
Mitigating Reward Hacking in RLHF via Bayesian Non-negative Reward Modeling
Toward Understanding Adversarial Distillation: Why Robust Teachers Fail
SpikingLM: Towards Fully Spiking Language Model
Learning Junta Distributions, Quantum Junta States, and QAC$^0$ Circuits
SmoothSpike: Spiking Transformer with Learnable Hadamard Transformation
AdaS: Adaptive Gradient Descent for Spiking Transformers
PASA: A Principled Embedding-Space Watermarking Approach for LLM-Generated Text under Semantic-Invariant Attacks
Generalizable and Composable Multi-Model Embedding Translation
Identifying Common Hubs in Multiple Gaussian Graphical Models
Mechanistic Interpretability as Statistical Estimation: A Variance Analysis
WAVE: Window-Aware Vocabulary-Efficient Early-Exit for Training-Free LLM Acceleration
Vector Linking via Cross-Model Local Isometric Consistency
Don't Force the Fit: Bounded Log-Likelihood Loss for Enhanced Reasoning in Large Language Models
LIMMT: Less Is More for Motion Tracking
$V_0$: A Generalist Value Model for Any Policy at State Zero
Accelerating Langevin Monte Carlo via Efficient Stochastic Runge-Kutta Methods beyond Log-Concavity
A Capacity-Based Rationale for Multi-Head Attention
Preference-based Antibody Expression Ranking: Scaling with Large-scale Weak Supervision
Scalable Power Sampling: Unlocking Efficient, Training-Free Reasoning for LLMs via Distribution Sharpening
A novel statistical approach to analyze image classification
TRACER: Trajectory Risk Aggregation for Critical Episodes in Agentic Reasoning
Efficient Diffusion Models via Time Step Optimization with Consistent Training and Inference Constraints
StepCodeReasoner: Aligning Code Reasoning with Stepwise Execution Traces via Reinforcement Learning
A Progressive Evidence Localization Framework Based on Wasserstein Gradient Flows for Document Visual Question Answering
FRACTAL: State Space Model with Fractional Recurrent Architecture for Computational Temporal Analysis of Long Sequences
Optimal Quantum Speedups for Repeatedly Nested Expectation Estimation
IndexMem: Learned KV-Cache Eviction with Latent Memory for Long-Context LLM Inference
Position: Agentic AI systems should be making Bayes-consistent decisions
Fingerprinting Pre-trained Encoders under Arbitrary Downstream Fine-Tuning via Adversarial Shifting
Adversarial Vulnerability from Interference Between Features in Superposition
Coarse-Grained Boltzmann Generators
A Time-Reparameterized Cumulative Intensity Extrapolation Sampler for Discrete Flow Matching
Information-Theoretic Disentangled Latent Modeling with Conditional Diffusion for Incomplete Multi-View Clustering
ForesightKV: Optimizing KV Cache Eviction for Reasoning Models by Learning Long-Term Contribution
rePIRL: Learn PRM with Inverse RL for LLM Reasoning
Disentangling Latent Risk Pathways via Bayesian Hypergraph Inference
Data Agent: Learning to Select Data via End-to-End Dynamic Optimization
Think Deep, Not Just Long: Measuring LLM Reasoning Effort via Deep-Thinking Tokens
Time series saliency maps: Explaining models across multiple domains
Refining Dual Spectral Sparsity in Transformed Tensor Singular Values
Is Data Shapley Not Better than Random in Data Selection? Ask NASH
OTora: A Unified Red Teaming Framework for Reasoning-Level Denial-of-Service in LLM Agents
CacheEdit: Efficient Multi-round Image Editing via Adaptive Token-wise Reuse.
Asymptotically Fast Clebsch-Gordan Tensor Products with Vector Spherical Harmonics
ThoughtFold: Folding Reasoning Chains via Introspective Preference Learning
Momentum Further Constrains Sharpness at the Edge of Stochastic Stability
In-Training Defenses Against Emergent Misalignment in Language Models
Finding DoRI: Discovery of Retained Images in Diffusion Models
StableVLA: Towards Robust Vision-Language-Action Models without Extra Data
Optimal and Scalable MAPF via Multi-Marginal Optimal Transport and Schrödinger Bridges
LiftQuant: Continuous Bit-Width Control for Pareto-Optimal LLM Deployment
Deep Residual Injection for Full-Spectrum Forensic Signal Perception in Multimodal Large Language Models
SLAP: The Semantic Least Action Principle for Variational Video-Language Modeling
DRIVE: Best Data Scheduling Practices for Reinforcement Learning with Verifiable Reward in Competitive Code Generation
Adaptive Estimation and Inference in Semi-parametric Heterogeneous Clustered Multitask Learning via Neyman Orthogonality
HDTree: Generative Modeling of Cellular Hierarchies for Robust Lineage Inference
Random Scaling of Emergent Capabilities
On Robustness and Chain-of-Thought Consistency of RL-Finetuned VLMs
T-measure: A Topology-Consistent Metric for Binary Segmentation
When Does Sparsity Mitigate the Curse of Depth in LLMs
Optimal Domain-Aware Privacy Mechanisms for Synthetic Data Generation
Riemannian MeanFlow
Breaking the Lock-in: Diversifying Text-to-Image Generation via Representation Modulation
Catch-22: On the Fundamental Tradeoff Between Detectability and Robustness in LLM Watermarking
Robust Strategic Classification under Decision-Dependent Cost Uncertainty
Smoothing Slot Attention Iterations and Recurrences
Rethinking Temporal Consistency in Video Object-Centric Learning: From Prediction to Correspondence
Quantifying LLM Attention-Head Stability: Implications for Circuit Universality
CHESS: Chebyshev Spectral Synthesis for Trajectory Condensation
WebWorld: A Large-Scale World Model for Web Agent Training
Contrastive Spectral Rectification: Test-Time Defense towards Zero-shot Adversarial Robustness of CLIP
A New Framework for Cybersecurity Refusals in AI Agents
Factored Latent Action World Models
Spurious Rewards: Rethinking Training Signals in RLVR
TDM-R1: Reinforcing Few-Step Diffusion Models with Non-Differentiable Reward
SafeHarbor: Defining Precise Decision Boundaries via Hierarchical Memory-Augmented Guardrail for LLM Agent Safety
SCALE: Self-uncertainty Conditioned Adaptive Looking and Execution for Vision-Language-Action Models
Sparse Autoencoders for Interpretable Emotion Control in Text-to-Speech
Provable Bounds for the Learnability of Sample-Compressible Families from Noisy Samples
Revisiting Photometric Ambiguity for Accurate Gaussian-Splatting Surface Reconstruction
Training-Trajectory-Aware Token Selection
VocSim A Training-free Benchmark for Zero-shot Content Identity in Single-source Audio
Controlled SDEs for Long-Horizon Motion Generation under Latent Decision Uncertainty
The Shadow Price of Reasoning: Economic Perspective on Optimal Budget Allocation for LLMs
Uncovering the Gradient Geometry of Long CoT: A Spectral-guided Approach to Reasoning Distillation
Deep sequence models tend to memorize geometrically; it is unclear why
Rational Transductors
Adalina: Adaptive Linear Approximation for the Shapley Value and Beyond
Faster Activation Functions at the Edge for Post-Training Speedups
Dense associative memory for Gaussian distributions
Robust Reinforcement Learning in a Sample-Efficient Setting
Structure-Centric Graph Foundation Model via Geometric Bases
Olaf-World: Orienting Latent Actions for Video World Modeling
Efficient Diffusion Models under Nonconvex Equality and Inequality constraints via Landing
Diversity Matters: Revisiting Test-Time Compute in Vision-Language Models
Any2Any: Unified Arbitrary Modality Translation for Remote Sensing
Reasoning on the Manifold: Bidirectional Consistency for Self-Verification in Diffusion Language Models
Towards Functional Correctness of Large Code Models with Selective Generation
Implicit Action Chunking for Smooth Continuous Control
PULSE: Generative Phase Evolution for Non-Stationary Time Series Forecasting
RA-VLA: Retrieval-Augmented VLA for Test-Time Adaptation
WaterSIC: information-theoretically (near) optimal linear layer quantization
Causal Effect Identifiability in the Presence of Latent Confounders Without Auxiliary Variables
Position: The AI Imperative: Scaling High-Quality Peer Review in Machine Learning
Just Y-Prediction: Enabling Historical Cumulative Inconsistency in Label Diffusion for Learning with Noisy Label
Orthogonal Model Merging
Beyond Generative Priors: Minority Sampling with JEPA-Guided Diffusion
LimiX-2M: Mitigating Low-Rank Collapse and Attention Bottlenecks in Tabular Foundation Models
Position: LLMs Should Incorporate Explicit Mechanisms for Human Empathy
Position: Text Embeddings Should Capture Implicit Semantics, Not Just Surface Meaning
Suppress and Diversify: Refining Robust Pathways for Corruption Robustness
CauseCollab: Causal Unified and Modality-Agnostic Network for Heterogeneous Collaborative Perception
One Model to Translate Them All: Universal Any-to-Any Translation for Heterogeneous Collaborative Perception
Categorical Flow Maps
Position: Accountable Deployment of Agentic AI Demands Layered, System-Level Interpretability
FIBER: A Differentially Private Optimizer with Filter-Aware Innovation Bias Correction
Effective Reasoning Chains Reduce Intrinsic Dimensionality
Particle-Guided Diffusion Models for Partial Differential Equations
Precise Asymptotics of Bagging Regularized M-estimators
ST-TGExplainer: Disentangling Stability and Transition Patterns for Temporal GNN Interpretability
Mitigating the Contractivity Trap in Diffusion ODEs via Stein Stabilization
Initialization is Half the Battle: Generating Diverse Images from a Guidance Potential Posterior
Position: LLM Agents Are the Antidote to Walled Gardens
IDRBench: Understanding the Capability of Large Language Models on Interdisciplinary Research
Position: Beyond Prediction: Toward Verifiable Physiological Waveform Reasoning with Foundation Models and Agentic LLMs
Beyond Accuracy: What Matters in Designing Well-Behaved Image Classification Models?
Attacks on Machine-Text Detectors Retain Stylistic Fingerprints
Position: Web Agents Should Use Typed Actions Instead of Click-Based Browsing
Controlled Dynamics Attractor Transformer
Constrained Flow Optimization via Sequential Fine-Tuning for Molecular Design
Training Diffusion Language Models for Black-Box Optimization
Unleashing the Representational Power of Fourier Shapes for Attacking Infrared Object Detection
Support-Proximity Augmented Diffusion Estimation for Offline Black-Box Optimization
INT vs. FP: A Comprehensive Study of Fine-Grained Low-bit Quantization Formats
Textual Supervision Enhances Geospatial Representations in Vision-Language Models
Language Generation in the Limit: Complexity Barriers and Implications for Learning
NanoFLUX: Distillation-Driven Compression of Large Text-to-Image Generation Models for Mobile Devices
PRIM：Cooperative Dynamic Token Compression for Efficient Large Multimodal Models
GOTabPFN: From Feature Ordering to Compact Tokenization for Tabular Foundation Models on High-Dimensional Data
Path-dependent Discrete Amortized Inference
Achieving Logarithmic Regret in KL-Regularized Zero-Sum Markov Games
Deterministic Differentiable Structured Pruning for Large Language Models
How Reasoning Evolves from Post-Training Data: An Empirical Study Using Chess
Routing by Reaching: Composition of Pre-trained GFlowNets for Multi-Objective Generation
Beyond Sunk Costs: Boosting LLM Pre-training Efficiency via Orthogonal Growth of Mixture-of-Experts
Position: Unplugging a Seemingly Sentient Machine Is the Rational Choice — A Metaphysical Perspective
NeuralFLoC: Neural Flow-Based Joint Registration and Clustering of Functional Data
FACT: Fuzzy Alignment with Comorbidity Topology for Reliable Multi-Label Medical Image Diagnosis
Is Fixing Schema Graphs Necessary? Full-Resolution Graph Structure Learning for Relational Deep Learning
When AI Benchmarks Plateau: A Systematic Study of Benchmark Saturation
Temporal Difference Learning with Compressed Updates: Error-Feedback meets Reinforcement Learning
Latent Diffusion Pretraining for Crystal Property Prediction
Self-Prompting Diffusion Transformer for Open-Vocabulary Scene Text Edit via In-Context Learning
InfoPO: Information-Driven Policy Optimization for User-Centric Agents
Learning Stochastic Bridges for Video Object Removal via Video-to-Video Translation
Comp-Attn: Present-and-Align Attention for Compositional Video Generation
BioDynaSpec: Harmonic-Guided Spatio-Spectral Autoregressive Diffusion for Protein Dynamics Generation
On the Limits of Test-Time Compute: Sequential Reward Filtering for Better Inference
A theory of learning data statistics in diffusion models, from easy to hard
A Solvable High-Dimensional Model Where Nonlinear Autoencoders Learn Structure Invisible to PCA While Test Loss Misaligns With Generalization
SteeringSafety: Benchmarking Representation Steering in LLMs Across Safety Perspectives
Understanding the Performance Gap in Preference Learning: A Dichotomy of RLHF and DPO
Design-Based Anytime-Valid Inference for Randomized Experiments with Delayed Outcomes and Staggered Entry
Two Modalities Are Better Than One: Efficient Adversarial Purification via Multimodal Diffusion Models
MAVRL: Learning Reward Functions from Multiple Feedback Types with Amortized Variational Inference
Regression Language Models for Code
Compute Where it Counts: Self Optimizing Language Models
The Cost of Information: Phase Transitions in Contextual Bandits with Paid Observations
Strategy Executability in Mathematical Reasoning: Leveraging Human–Model Differences for Effective Guidance
Can LLMs Reason Structurally? Benchmarking via the lens of Data Structures
Comparing Deterministic and Soft Policy Gradients for Optimizing Gaussian Mixture Actors
MotionGRPO: Overcoming Low Intra-Group Diversity in GRPO-Based Egocentric Motion Recovery
TimeRewarder: Learning Dense Reward from Passive Videos via Frame-wise Temporal Distance
FAIR-Calib: Frontier-Aware Instability-Reweighted Calibration for Post-Training Quantization of Diffusion Large Language Models
FuseFSS: Efficient Secure LLM Inference with Function Secret Sharing
Utility Boundary of Dataset Distillation: Scaling and Coverage Laws
WarmServe: Enabling One-for-Many GPU Prewarming for Multi-LLM Serving
Probing RLVR Training Instability through the Lens of Objective-Level Hacking
Scaling Real-World Robot Policy Evaluation via Discrete Diffusion World Model
MVISTA-4D: View-Consistent 4D World Model with Test-Time Action Inference for Robotic Manipulation
Position: Explainability Research Must Prioritize Foundations over Ad-hoc Methods
TimeAutoDiff: A Unified Framework for Generation, Imputation, Forecasting, and Time-Varying Metadata Conditioning of Heterogeneous Time Series Tabular Data
AutoQRA: Joint Optimization of Mixed-Precision Quantization and Low-rank Adapters for Efficient LLM Fine-Tuning
Degradation-Aware Metric Prompting for Hyperspectral Image Restoration
Adaptive Memory Retention in Dynamic Graphs
LAVA: A Unified Framework for Finetuning Language and Vision Models
Know More, Know Clearer: A Meta-Cognitive Framework for Knowledge Augmentation in Large Language Models
Beyond Trajectory-Level Attribution: Graph-Based Credit Assignment for Agentic Reinforcement Learning
Trajectory-Level Speculative Decoding for Diffusion Language Models
Protein Design with Agent Rosetta: A Case Study for Specialized Scientific Agents
Weak-to-Strong Generalization via Bregman Bias–Variance Decomposition
Condition Number Based Low-Bit Quantization for Image Super-Resolution
SURGE: Surrogate Gradient Adaptation in Binary Neural Networks
Distinguishable Deletion: Unifying Knowledge Erasure and Refusal for Large Language Model Unlearning
Policies Permitting LLM Use for Polishing Peer Reviews Are Currently Not Enforceable
Adaptive Utilization of Low-Rank Adaptation via Conditioned Gating
FloorplanQA: A Benchmark for Spatial Reasoning in LLMs using Structured Representations
Geometric Embedding Alignment via Curvature Matching in Transfer Learning
Calibrated Preference Learning: The Case of Label Ranking
Evolution Strategies at the Hyperscale
Causal-Adapter: Taming Text-to-Image Diffusion for Faithful Counterfactual Generation
Active Tabular Augmentation via Policy-Guided Diffusion Inpainting
Making Expert Reasoning Learnable with Self-Distillation
ClinTutor-R1: Advancing Scalable and Robust One-to-Many Alignment in Clinical Socratic Education
TRACE: Toulmin-based Reasoning Assessment through Constructive Elements for LLM CoT Evaluation
FedPDG: Prediction Discrepancy–Guided Data Generation for Heterogeneous Federated Learning
VEQ: Modality-Adaptive Quantization for MoE Vision-Language Models
Dynamic Relational Priming Improves Transformer in Multivariate Time Series
Softsign: Smooth Sign in Your Optimizer For Better Parameter Heterogeneity Handling
SparseInfer: Accelerating Large Language Model Inference with Semantics-Inspired Adaptive Sparse Activation
DisPOSE: Projected Polystochastic Diffusion for Self-Supervised Multi-View 3D Human Pose Estimation
Mosaic: Runtime-Efficient Multi-Agent Embodied Planning
One LR Doesn’t Fit All: Heavy-Tail Guided Layerwise Learning Rates for LLMs
Enhancing Numerical Prediction in LLMs via Smooth MMD Alignment
From Optimization to Generalization under Heavy-Tailed Data: The Role of Gradient Clipping
Reasoning Compartmentalization: Bridging the Concretization Gap via Abstraction-based Routing
HoloFair: Unified T2I Fairness Evaluation and Fair-GRPO Debiasing
VisionPulse: Dynamic Visual Sparsity for Efficient Multimodal Reasoning
PGC: Peak-Guided Calibration for Generalizable AI-Generated Image Detection
Learning multi-modal generative models with permutation-invariant encoders and tighter variational objectives
DataGuard: A Non-intrusive Dataset Auditing Framework via Differential Information Forensics
Collaborative likelihood-ratio estimation over graphs
NorMuon: Making Muon more efficient and scalable
Mitigating Error Propagation in Low-Rank Approximation of Large Models via Distribution-Aware Whitening
Mind the Gap: Mixtures of Gaussians in Approximate Differential Privacy
Reasoning Structure of Large Language Models
On the Generalization in Topology Optimization via Sensitivity-Conditioned Bernoulli Flow Matching
Neural-HSS: Hierarchical Semi-Separable Neural PDE Solver
Beyond Text-to-SQL: Can LLMs Really Debug Enterprise ETL SQL?
Statistical Early Stopping for Reasoning Models
FLAG: Foundation model representation with Latent diffusion Alignment via Graph for spatial gene expression prediction
SpatialReward: Bridging the Perception Gap in Online RL for Image Editing via Explicit Spatial Reasoning
A Linearly Convergent Proximal Subgradient Algorithm for Sparse Portfolio Optimization with Transaction Cost
PCGS: Deblurring 3D Gaussian Splatting with Patch Comparison
EngiAgent: Fully Connected Coordination of LLM Agents for Solving Open-ended Engineering Problems with Feasible Solutions
Are Common Substructures Transferable? Riemannian Graph Foundation Model with Neural Vector Bundles
Propose, Solve, Verify: Self-Play Through Formal Verification
Learning-Augmented Scalable Linear Assignment Problem Optimization via Neural Dual Warm-Starts
Fast Spectrally Sparse Signal Reconstruction via Jacobi-Preconditioned Gradient Descent
Reinforcement Learning from Human Feedback with Active Queries
TRACE: Trajectory Recovery for Continuous Mechanism Evolution in Causal Representation Learning
QiMeng-PerceptOS: Semantic-Aware Kernel Optimization for OS-Intensive Workloads via Hardware-Software Alignment
When the Prompt Becomes Visual: Vision-Centric Jailbreak Attacks for Large Image Editing Models
PATCHCODE: Discrete Latent Predictive Learning for EEG Foundation Model
Asymmetric Prompt Weighting for Reinforcement Learning with Verifiable Rewards
Asymmetric Perturbation in Solving Bilinear Saddle-Point Optimization
Large-scale Uncertainty Quantification for Latent Variable Models Using Subsampling Markov Chain Monte Carlo
Curriculum-Guided Layer Scaling for Language Model Pretraining
GeoEvo: Identity-Aware Potential Game with Geometric Evolution for Personalized Multimodal Federated Learning
The Flexibility Trap: Rethinking the Value of Arbitrary Order in Diffusion Language Models
From Associations to Activations: Comparing Behavioral and Hidden-State Semantic Geometry in LLMs
Multimarginal flow matching with optimal transport potentials
DecAEvolve: Decompose, Adapt, and Evolve for Effective LLM-based Scientific Equation Discovery
Rubric Curriculum RL: Exploiting the Generation-Verification Gap in Non-Verifiable Domains
Beyond Gemini-3-Pro: Revisiting LLM Routing and Aggregation at Scale
UniScale: Adaptive Unified Inference Scaling via Online Joint Optimization of Model Routing and Test-Time Scaling
Token-Sparse Medical Multimodal Reasoning via Dual-Stream Reinforcement Learning
CAT-Q: Cost-efficient and Accurate Ternary Quantization for LLMs
Position: LLM Benchmark Datasets should be Contamination-Resistant
When Labelers Stay Silent: The Power of Ties in Cost-Effective Preference Learning
Robust Multi-View Fusion via Prototype-Anchored Unbalanced Optimal Transport
OXE-AugE: A Large-Scale Robot Augmentation of OXE for Scaling Cross-Embodiment Policy Learning
CatFlow: Co-generation of Slab-Adsorbate Systems via Flow Matching
Unbiased Alignment for Large Language Models with Noisy Preferences
Alignment Tampering: How Reinforcement Learning from Human Feedback Is Exploited to Optimize Misaligned Biases
Geometry-Aware Image Flow Matching
RePro: Training Language Models to Faithfully Recycle the Web for Pretraining
From Outcomes to Actions: Leveraging Hindsight for Long-Horizon Language Agent Training
Diffusing to Coordinate: Efficient Online Multi-Agent Diffusion Policies
Data Selection for Fine-tuning Vision Language Models via Cross Modal Alignment Trajectories
VideoTemp-o3: Harmonizing Temporal Grounding and Video Understanding in Agentic Thinking-with-Videos
Learning Credal Ensembles via Distributionally Robust Optimization
Breaking the Capacity Bottleneck in Model-Heterogeneous Federated Learning via Gradual Model Restoration
TextMesh4D: Zero-shot Text-to-4D Mesh Generation
Sparse Models, Sparse Safety: Unsafe Routes in Mixture-of-Experts LLMs
UHR-BAT: Budget-Aware Token Compression Vision-Language model for Ultra-High-Resolution Remote Sensing
From LLM-Generated Conjectures to Lean Formalizations: Automated Polynomial Inequality Proving via Sum-of-Squares Certificates
MePo: Meta Post-Refinement for Rehearsal-Free General Continual Learning
Preserving Expert-Level Privacy in Offline Reinforcement Learning
Unbiased and Second-Order-Free Training for High-Dimensional PDEs
Differentially Private and Scalable Estimation of the Network Principal Component
ConPress: Learning Efficient Reasoning from Multi-Question Contextual Pressure
Skip a Layer or Loop It? Learning Program-of-Layers in LLMs
Certified Circuits: Stability Guarantees for Mechanistic Circuits
Improving Visual Token Reduction via Rectifying Distortions for Efficient Multimodal LLM Inference
CalM: A Self-Supervised Foundation Model for Population Dynamics in Calcium Imaging Data
Memory Savings at What Cost? A Study of Alternatives to Backpropagation
ExPLAIND: Unifying Model, Data, and Training Attribution to Study Model Behavior
CLINIC: Towards High-quality Graph Out-Of-Distribution Detection
CELL: A Causal Perspective for Fairness-aware Graph Adaptation
Zero Sum SVD: Balancing Loss Sensitivity for Low Rank LLM Compression
CURE: Context-driven Diffusion with Progressive Expansion for Single Domain Generalization in Time Series Classification
Enhancing Affine Maximizer Auctions with Correlation-Aware Payment
Pushing the Boundaries of Natural Reasoning: Interleaved Bonus from Formal-Logic Verification
Small Generalizable Prompt Predictive Models Can Steer Efficient RL Post-Training of Large Reasoning Models
Random Selection Reveals Implicit Knowledge Consensus in Code Generation
Towards High-Fidelity CAD Generation via LLM-Driven Program Generation and Text-Based B-Rep Primitive Grounding
Faster Query-Key Learning Sharpens Attention in Self-Attention Models
Attention with Routed-Memory for Learnable Sparse Control
Radial Scaling Voxelization for Accurate Small Object 3D Detection
Why Are Linear RNNs More Parallelizable?
LLM-MatLogic: Executable Exchange Contracts for Knowledge-Graph Query Answering with Scoped Negation
SPHERE: Mitigating the Loss of Spectral Plasticity in Mixture-of-Experts for Deep Reinforcement Learning
PDFBench: A Benchmark for De Novo Protein Design from Function
CoEvol-NO: State and Coordinate Co-Evolution with an Error-Driven Predictor-Corrector Paradigm for Neural Operator Transformer
Nested Spatio-Temporal Time Series Forecasting
Decision-Focused Learning via Tangent-Space Projection of Prediction Error
PinTok: Tokenizers Deserve Dedicated Pinned CPU-Compute and Memory
Rethinking Attention in Spiking Transformers: Overcoming Density Bias with Set Similarity
OmniMoE: An Efficient MoE by Orchestrating Atomic Experts at Scale
OmniShow: Unifying Multimodal Conditions for Human-Object Interaction Video Generation
Dynamics Are Learned, Not Told: Semi-Supervised Discovery of Latent Dynamics Geometries For Zero-Shot Policy Adaptation
Bridging the Stability-Expressivity Gap: Synthetic Data Scaling and Preference Alignment for Low-Resource Spoken Language Models
Transport and Merge: Cross-Architecture Merging for Large Language Models
How to Correctly Report LLM-as-a-Judge Evaluations
Learning Transferable Interaction Primitives from Game Videos for Humanoid Locomotion
Meta-learning Structure-Preserving Dynamics
A Regret Minimization Framework on Preference Learning in Large Language Models
Learning Treatment Allocations with Risk Control Under Partial Identifiability
LASER: Learning Active Sensing for Continuum Field Reconstruction
Harnessing Uncertainty: Entropy-Modulated Policy Gradients for Long-Horizon LLM Agents
TabularBERT: Binning-Based Self-Supervised Learning for Tabular Representation
A Call to Lagrangian Action: Learning Population Mechanics from Temporal Snapshots
BLIPs: Bayesian Learned Interatomic Potentials
Investigating Memory in RL with POPGym Arcade
ALAS: Additive Learnable Alpha-Stable Kernels for Flexible Bayesian Optimization
On the Computational Complexity of Performative Prediction
Less Is More in Federated Continual Learning: RieSelect for Conflict-Aware Layer Selection in LLMs
ST-Veto: Spatio-Temporal Token Veto for Diffusion MLLMs via Taylor Prediction and Visual Grounding
Doubly Outlier-Robust Online Infinite Hidden Markov Model
Is Task-Specific Training Necessary for Anomaly Detection?
Plug-and-Play Benchmarking of Reinforcement Learning Algorithms for Large-Scale Flow Control
CoverPruneGS: Coverage-Preserving Structured Pruning for Hierarchical 3D Gaussian Splatting from Sparse-View Monocular Videos
Hyperspectral Image Fusion with Spectral-Band and Fusion-Scale Agnosticism
Butterworth as Attention: Anisotropic Spectral Gating for Pansharpening
FairJudge : An Adaptive, Debiased, and Consistent LLM-as-a-Judge
Beyond Heuristics: Learnable Density Control for 3D Gaussian Splatting
Large-capacity and Receiver Authenticable Generative Image Steganography
How to Fine-Tune a Reasoning Model? A Teacher–Student Cooperation Framework to Synthesize Student-Consistent SFT Data
Fix Before Search: Benchmarking Agentic Visual Query Pre-processing in Multimodal Retrieval-augmented Generation
Towards Realistic Lifelong Re-identification: Identity Recurrence with Changing Clothes
Coverage Improvement and Fast Convergence of On-policy Preference Learning
Diffuse to Detect: Bi-Level Sample Rebalancing with Pseudo-Label Diffusion for Point-Supervised Infrared Small-Target Detection
Improving Adversarial Robustness of Attribution via Implicit Regularization
Do LLMs “Feel”? Emotion Circuits Discovery and Control
The Hidden Cost of Structured Generation in LLMs: Draft-Conditioned Constrained Decoding
AgentWebBench: Benchmarking Multi-Agent Coordination in Agentic Web
Sentinel-VLA: A Metacognitive VLA Model with Active Status Monitoring for Dynamic Reasoning and Error Recovery
Fast and Highly Expressive Policy Learning for Offline Reinforcement Learning via Bootstrapped Flow Q-Learning
IQA-Spider: Unifying Multi-Granularity Image Quality Assessment with Reasoning, Grounding and Referring
Bridging the Grounding Gap in VideoQA via Typed Memory for Language-based Belief-State Reasoning
Simultaneous Speech-to-Speech Translation Without Aligned Data
QuantWear: Quantum-scale Wear Particle Detection for Jet Engine Diagnosis
Neuro-Symbolic AI for Analytical Solutions of Differential Equations
Towards Effective Waste Segmentation for Automated Waste Recycling in Cluttered Background
GADA: Geometry-Aware Deformable Aggregation for Image-Based Gaussian Splatting
GenCircuit-RL: Reinforcement Learning from Hierarchical Verification for Genetic Circuit Design
Rethinking Low-Confidence Pseudo Labels: Influence-Aware Semi-Supervised Fine-Tuning for Hyperspectral Change Detection
Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants
CGSVD: Cascaded Granular Singular Value Decomposition for Large Language Model Compression
Breaking Multi-Task Curse: Reward-Weighted Evolution for Black-Box Many-Task Optimization
RealtimeTool: Parallel Decoding for Real-Time LLM Function Calling
Pix2Key: Controllable Open-Vocabulary Retrieval with Semantic Decomposition and Self-Supervised Visual Dictionary Learning
DiScoFormer: Plug-In Density and Score Estimation with Transformers
Adaptive Querying with AI Persona Priors
PCRNet: Phase-aware Complex Refinement Network for EEG-based Auditory Attention Decoding
StretchTime: Adaptive Time Series Forecasting via Symplectic Attention
Genome-Factory: A Library for Tuning, Deploying, and Interpreting Genomic Foundation Models
End-to-End Compression for Tabular Foundation Models
SoftMatcha 2: A Fast and Soft Pattern Matcher for Trillion-Scale Corpora
PyHealth 2.0: A Comprehensive Open-Source Toolkit for Accessible and Reproducible Clinical Deep Learning
Stable Localized Conformal Prediction via Transduction
A Short and Unified Convergence Analysis of the SAG, SAGA, and IAG Algorithms
Beyond Static Endpoints: Tool Programs as an Interface for Flexible Agentic Web Services
DNA: Uncovering Universal Latent Forgery Knowledge
Exact Unlearning in Reinforcement Learning
Multi-Head LatentMoE and Head Parallel: Communication-Efficient and Deterministic MoE Parallelism
FlatLab: A Unified Methodology Framework and Simulation-Based Benchmark for Robotic Manipulation of Flat Objects
Debate2Create: Robot Co-design via Multi-Agent LLM Debate
PlugGuard: A Streaming Safeguard for Large Models via Latent Dynamics-Guided Risk Detection
Rethinking the Trust Region in LLM Reinforcement Learning
HDFlow: Hierarchical Diffusion-Flow Planning for Long-horizon Tasks
Unbiased Principles, Robust Rewards
Efficient Code Analysis via Graph Representation Learning-Guided Large Language Models
SI-IGCL: Subject Invariance-aware Inverse Graph Contrastive Learning for Psychiatric Disorder Identification
RSPO: Regularized Self-Play Alignment of Large Language Models
EcoVLA: Environment-Aware Adaptive Pruning with Interleaved Inference Orchestration for Vision-Language-Action Models
Generalizable and Actionable Parts Pose Estimation with Symmetry Annotation-Free Learning Strategy
RDT2: Exploring the Scaling Limit of UMI Data Towards Zero-Shot Cross-Embodiment Generalization
Position: Predictive Uncertainty Is Not Enough -- Joint Distribution for Full Uncertainty Representation
Compile to Compress: Boosting Formal Theorem Provers by Compiler Outputs
Robust Stochastic Gradient Posterior Sampling with Lattice Based Discretisation
VLANeXt: Recipes for Building Strong VLA Models
Process Reward Models That Think
DynVLA: Learning World Dynamics for Action Reasoning in Autonomous Driving
Supervised Graph Contrastive Learning for Gene Regulatory Networks
Convergence Rate of the Last Iterate of Stochastic Proximal Algorithms
Solving Stochastic Variational Inequalities without the Bounded Variance Assumption
Learning Permutation Distributions via Reflected Diffusion on Ranks
Distinguishing Imitation Error from Intrinsic Motion Learning Difficulty
DecoVer: A Decompose-and-Verify Neuro-Symbolic Framework for Embodied Task Planning with BC+
ScoreMix: Synthetic Data Generation by Score Composition in Diffusion Models Improves Recognition
World Models in Pieces: Structural Certification for General Agents
Plan in Sandbox, Navigate in Open Worlds: Learning Physics-Grounded Abstracted Experience for Embodied Navigation
Learning Hamiltonian Flow Maps: Mean Flow Consistency for Large-Timestep Molecular Dynamics
Continual Model Routing in Evolving Model Hubs
Controllable and Explainable Personality Sliders for LLMs at Inference Time
Multi-Objective Learning for Diffusion Models: A Statistical Theory under Semi-Supervised Learning
Vision-Language-Action Pretraining from Large-Scale Human Videos
ECo-MoE: Embodiment-Conditioned Mixture of Experts Increases the Evolvability of Robots
Generative Augmented Inference
DeepSight: Long-Horizon World Modeling via Latent States Prediction for End-to-End Autonomous Driving
Personalized Policy Learning through Discrete Experimentation
Keep Everyone Happy: Online Fair Division of Numerous Items with Few Copies
A Generalist Pair-wise Progress Critic Model for Vision-Language-Action Robots
Collaborative Threshold Watermarking
TimeSeed: Effective Time Series Forecasting with Sparse Endogenous Variables
RoboOmni: Actions Are Just Another Modality for Vision-Language Models
Convex Basins in Single-Index Model Loss Landscapes: Applications to Robust Recovery under Strong Adversarial Corruption
Learning the ESG Geometry with Domain Aware Language Models
Functional Cache Grafting: Robust and Rapid Code-Policy Synthesis for Embodied Agents
MEMO: Memory-Augmented Model Context Optimization for Robust Multi-Turn Multi-Agent LLM Games
Multivariate Distributional Reinforcement Learning Using Sliced Divergences
Plug-and-Play Label Map Diffusion for Universal Goal-Oriented Navigation
VLA-ATTC: Adaptive Test-Time Compute for VLA Models with Relative Action Critic Model
Gateways to Tractability for Satisfiability in Pearl’s Causal Hierarchy
Post-Training Language Models for Crosslingual Consistency
Learning Gaussian Graphical Models from a Glauber Trajectory Without Mixing
SpikeVLA: Vision-Language-Action Models with Spiking Neural Networks
A KL-regularization framework for learning to plan with adaptive priors
Transforming Weather Data from Pixel to Latent Space
Think Less, Act Early: Reinforced Latent Reasoning with Early Exit in Vision-Language-Action Models
EvoCF: Multi-Agent Collaboration via Agentic Memory-Driven Evolutionary Counterfactual Planning
Time-Series Decomposition as a Standalone Task: A Mechanism-Driven Diagnostic Benchmark
PonderLM-2: Pretraining LLM with Latent Thoughts in Continuous Space
Lower Complexity Bounds for Nonconvex-Strongly-Convex Bilevel Optimization with First-Order Oracles
STFlow: Data-Coupled Flow Matching for Geometric Trajectory Simulation
Attentive Multi-Layer Fusion for Vision Transformers
Channel Adapter for Time Series Foundation Models in Zero-Shot Multivariate Forecasting
LAPRAS : Learning-Augmented PRivate Answering for linear query Streams.
Angel or Demon: Investigating the Plasticity Interventions' Impact on Backdoor Threats in Deep Reinforcement Learning
Native Active Perception as Reasoning for Omni-Modal Understanding
EnsembleVLA: Ensemble Learning for Vision-Language Action Models
MineDraft: A Framework for Batch Parallel Speculative Decoding
Artemis: Structured Visual Reasoning for Perception Policy Learning
Deep Trajectory Supervision: Deep Supervision Strikes Back
Holonomy Grid Codes for Generalisation Under Directed Actions
R1-SyntheticVL: Is Synthetic Data from Generative Models Ready for Multimodal Large Language Model?
GeoReward: Mitigating Contextual Variable Overestimation in Vision-Language Models for Cross-Market Preference Prediction
Noisy-Channel Minimum Bayes Risk Decoding
Milestone-Guided Policy Learning for Long-Horizon Language Agents
Transferable Reinforcement Learning via Probabilistic Latent Embeddings and Dynamic Policy Adaptation for Sim-to-Real Deployment
Multi-view Consistent Latent Action Learning for World Modeling and Control
Learn to change the world: Multi-level reinforcement learning with model-changing actions
Distributional Open-Ended Evaluation of LLM Cultural Value Alignment Based on Value Codebook
Generalization Bounds for Out-of-distribution Generalization
Beyond the Proxy: Trajectory-Distilled Guidance for Offline GFlowNet Training
On Learnability and Disambiguation of Multiclass Partial Concept Classes
Conformal Prediction for Early Stopping in Mixed Integer Optimization
A Machine-Learned Comorbidity Index
Geometry-Misalignment in Distributional Learning
PipeSD: An Efficient Cloud-Edge Collaborative Pipeline Inference Framework with Speculative Decoding
Identifiable Nonlinear Differentiable Causal Discovery via Independence and Adaptive Group Sparsity
Artificial Hippocampus Networks for Efficient Long-Context Modeling
M-Star: Markovian Projection of Star-Shaped Diffusion for Exponential Family Distributions
$f$-Trajectory Balance: A Loss Family for Tuning GFlowNets, Generative Models, and LLMs with Off- and On-Policy Data
Minibatch selection for Language Models via Partition Matroid Constrained Gradient Matching
Adapting Noise to Data: Generative Flows from Learned 1D Processes
Causal-EPIG: Causally Aligned Active CATE Estimation
ExVerus: Verus Proof Repair via Counterexample Reasoning
Removing Noise, not Finding Gold: Quality Filtering for Large-Scale Pretraining
AgentLAB: Benchmarking LLM Agents against Long-Horizon Attacks
Value Aggregation with Uncertainty in Online Decentralized MARL
Can Vision Language Models Learn Intuitive Physics from Interaction?
DITRON: Distributed Multi-level Tiling Compiler for Parallel Tensor Programs
HEXST: Hexagonal Shifted-Window Transformer for Spatial Transcriptomics Gene Expression Prediction
RADAR: Redundancy-Aware Diffusion for Multi-Agent Communication Structure Generation
LineageFlow: Flow Matching for High-Fidelity Family-Aware Protein Sequence Generation
Positive-Unlabeled Learning with Extreme Scarcity of Labeled Positives
NeurIPS: Neuro-anatomical Inductive Priors for Sphere-based Brain Decoding
FedARC: Anchor-Guided Residual Compensation for Data and Model Heterogeneous Federated Learning
The Data Manifold under the Microscope
DreamDojo: A Real-Time Robot World Model from Large-Scale Human Videos
Thinking in Structures: Evaluating Spatial Intelligence in Constraint-Governed Spaces
Geometric Conformal Prediction with Spatial Ranks and Multivariate Quantiles
Short Chains, Deep Thoughts: Balancing Reasoning Efficiency and Intra-Segment Capability via Split-Merge Optimization
Divide-and-Denoise: A Game-Theoretic Method for Fairly Composing Diffusion Models
Dismantling the Illusion of Vision-Language-Action Models Competence via Explicit Distributional Shifts
FIPN: Forward Self-Organizing Interpretable Polynomial Networks for Time Series Forecasting
Uncertainty-Aware Clarification in LLM Agents with Information Gain
Video-OPD: Efficient Post-Training of Multimodal Large Language Models for Temporal Video Grounding via On-Policy Distillation
Positive–Unlabeled Reinforcement Learning Distillation for On-Premise Small Models
TraCeS: Learning Per-Timestep Constraint-Violation Credit from Sparse Trajectory-Level Labels
Semantic Tube Prediction: Beating LLM Data Efficiency with JEPA
Expandable, Compressible, Mineable: Open-World Thermal Infrared Image Restoration
Memory-Efficient LLM Training with Dynamic Sparsity: From Stability to Practical Scaling
Inconsistency-Aware Minimization: Improving Generalization with Unlabeled Data
Temporal Difference Learning for Diffusion Models
The Invisible Lottery: How Subtle Cues Steer Algorithm Choice in LLM Code Generation
Controlled Collaboration Geometry for Personalized Federated Learning
Autoregressive Boltzmann Generators
Robust Parallel Diffusion Sampling via Dynamic Jacobian Bandwidth
MOD-SR: Unifying Multimodal Learning and Direct Optimization with Gradient-Guided Diffusion Model for Symbolic Regression
MemEvolve: Meta-Evolution of Agent Memory Systems
DOCKSMITH: Scaling Reliable Coding Environments via an Agentic Docker Builder
LoKiFormer: Locality-aware Attention with Decoupled Knowledge Memory for Efficient Large Language Model Pretraining
Video-o3: Native Interleaved Clue Seeking for Long Video Multi-Hop Reasoning
Reinforcement Fine-Tuning Naturally Mitigates Forgetting in Continual Post-Training
An Evidential Route to Asymptotic Bayes Optimality under Sparsity
Active Policy Optimization for Individualized Dosing via Gradient Variance Minimization
Measurement-Consistent Langevin Corrector for Stabilizing Latent Diffusion Inverse Problem Solvers
SWE-Perf: Can Language Models Optimize Code Performance on Real-World Repositories?
Powerful and Theoretically Guaranteed Independence Testing on Heterogeneous Federated Clients
Feasible Fusion: Constrained Joint Estimation under Structural Non-Overlap
A Noise Sensitivity Exponent Controls Large Statistical-to-Computational Gaps in Single- and Multi-Index Models
Once-for-All: Scalable Simultaneous Forecasting via Equilibrium State Estimation
Learning Reward–Cost Balance in Safe RL via Score-Based World Models
Detecting Perspective Shifts in Multi-Agent Systems
FlowBot: Inducing LLM Workflows with Bilevel Optimization and Textual Gradients
Adaptive Multi-Round Allocation with Stochastic Arrivals
Beyond Majority Voting: LLM Aggregation by Leveraging Higher-Order Information
EvReflection: Event-Driven Micro-Dynamics for Reflection Removal
Transformer Circuits Can Realize Clustering Algorithms
Elastic Attention: Test-time Adaptive Sparsity Ratios for Efficient Transformers
Parametrized Power-Iteration Clustering for Directed Graphs
Dual-Calibration Multi-View Clustering via Compact Anchor Learning
Beyond Logits: Coherent Hallucination Mitigation via Attention Contrastive Decoding
RoboFlow4D: A Lightweight Flow World Model Toward Real-Time Flow-Guided Robotic Manipulation
Position: Uncertainty Quantification in LLMs is Just Unsupervised Clustering
FS-I2P: A Hierarchical Focus–Sweep Registration Network with Dynamically Allocated Depth
Identifiable Token Correspondence for World Models
Reward Shaping Control Variates for Off-Policy Evaluation Under Sparse Rewards
Spectral Heat Flow for Conservative Token Condensation in Vision-Language Models
CURE: Consistency-under-Unified Semantic Regularization for Generalized Category Discovery
Plug-and-Play Diffusion Meets ADMM: Dual-Variable Coupling for Robust Medical Image Reconstruction
Resolving Blind Inverse Problems under Dynamic Range Compression via Structured Forward Operator Modeling
Polyphonia: Zero-Shot Timbre Transfer in Polyphonic Music with Acoustic-Informed Attention Calibration
Deep Multi-view Graph Clustering via Attribute-aware Bidirectional Structural Refinement and Pseudo-label Guided Multi-level Fusion
LitReview Arena: Evaluating Literature Review Agents with Battle-style Peer Review Platform
Beyond Independence: Learning Correlated Views for Variational Incomplete Multi-View Clustering
MAGIC: Multi-Granularity Language-Informed Image Clustering
Beyond Literal Translation: Evaluating Cultural Effectiveness in Social Media UGC
TSP with Predictions: Heatmap to Tour with Provable Guarantees
GASS: Geometry-Aware Spherical Sampling for Disentangled Diversity Enhancement in Text-to-Image Generation
Signal Strength Estimation in Logistic Regression Using Data Splitting
Gradient Descent as a Perceptron Algorithm: Understanding Dynamics and Implicit Acceleration
Timestep Rescheduling in Diffusion Inversion
Regularized Discriminative Alignment for Deep Representations under Label Shift
StyleDistillation: A New Insight of Image Style Enables Personalized Aesthetic Manipulation
Self-Soupervision: Cooking Model Soups without Labels
Private and Stable Test-time Adaptation with Differential Privacy
PRISM: Synergizing Vision Foundation Models via Self-organized Expert Specialization
One-Step Gradient Delay is Not a Barrier for Large-Scale Asynchronous Pipeline Parallel LLM Pretraining
DeepBlip: Estimating Conditional Average Treatment Effects Over Time
$\tau^2$-Bench: Evaluating Conversational Agents in a Dual-Control Environment
Beyond Point Predictions: Manifold Expansion and Dual Alignment for Robust Time Series Distillation
MRPO: Magnitude-Regularized Policy Optimization via L1 Constraints
How Do Language Models Speak Languages? A Case Study on Unintended Code-Switching
Trifuse: Enhancing Attention-Based GUI Grounding via Multimodal Fusion
SKETCH: Semantic Key-Point Conditioning for Long-Horizon Vessel Trajectory Prediction
Power-Boosted Granger-Causal Discovery for Large Heterogeneous Panel Data
Automatic Unsupervised Ensemble Outlier Model Selection
Tuning-Free One-Class Discriminant Learning for Tabular Anomaly Detection
SIMPC: Learning Self-Induced Mirror-Point Consistency for Unsupervised Point Cloud Denoising
Alethia: a Foundational Encoder for Voice Deepfakes
Position: AI for Science Should Treat Measurement-to-Dataset Pipelines as Inference Components
Beyond Global Alignment: Fine-Grained Motion-Language Retrieval via Pyramidal Shapley-Taylor Learning
Learning Context-Conditioned Predicate Semantics via Prototype Feedback
Noise-Robust Density Estimation for Tabular Data Anomaly Detection
RAST-MoE-RL: A Regime-Aware Spatio-Temporal MoE Framework for Deep Reinforcement Learning in Ride-Hailing
SFedPO: Streaming Federated Learning with a Prediction Oracle under Temporal Shifts
Compress then Merge: From Multiple LoRAs into One Low-Rank Adapter
Student-Centered Distillation Narrows the Agentic Gap Between Small and Large LLMs
One Intervention per Component is Enough: Towards Identifiability in Linear Stochastic Dynamics from Steady State
The Theory and Practice of MAP Inference over Non-Convex Constraints
VisualScore: Learning Holistic Visual Quality Scores via Multi-Task Reasoning
Compact Conformal Subgraphs
Prompt Estimation from Prototypes for Federated Prompt Tuning of Vision Transformers
Unveiling the Visual Counting Bottleneck in Vision-Language Models
MIND: Multi-rationale INtegrated Discriminative Reasoning Framework for Multi-modal Large Models
Matroid Algorithms Under Size-Sensitive Independence Oracles
Gradient Testing and Estimation by Comparisons
FOCUS: Forcing In-Context Object Localization through Visual Support Constraints and Policy Optimization
Romberg-Extrapolated Zeroth-Order Gradient Estimator: Higher-Order Bias Reduction with Preserved Leading Directional Variance
Exploiting Hankel-Toeplitz Structures for Fast Computation of Kernel Precision Matrices
GHOST: Geometry-Guided Hallucination of Opaque Surface Textures
CurvZO: Adaptive Curvature-Guided Sparse Zeroth-Order Optimization for Efficient LLM Fine-Tuning
Position: Stop Preaching and Start Practising Data Frugality for Responsible Development of AI
X-MoGe: A Cross-Modal Adaptation Framework with Mixture-of-Experts and Geometry Guidance for Heterogeneous Collaborative Perception
Semi-Supervised Learning with Noisy Proxy Covariates: Generalization Bounds and Distribution Regression
Taking the GP Out of the Loop
XSkill: Continual Learning from Experience and Skills in Multimodal Agents
Predicting the Order of Upcoming Tokens Improves Language Modeling
JAEGER: Joint 3D Audio-Visual Grounding and Reasoning in Simulated Physical Environments
Why Tree-Style Branching Matters for Thought Advantage Estimation in GRPO
When More Data Doesn't Help: Limits of Adaptation in Multitask Learning
Head-in-Head in Linear Attention
Position: Modular Safety Guardrails Are Necessary for Foundation-Model-Enabled Robots in the Real World
Verified SHAP: Provable Bounds for Exact Shapley Values of Neural Networks
Position: Benchmarks for Vision–Language Models in Urban Perception Should Be Reliability-Aware and Negotiated
Global Plane Waves from Local Gaussians: Periodic Charge Densities in a Blink
EAPO: Enhancing Policy Optimization with On-Demand Expert Assistance
Preference Goal Tuning: Post-Training as Latent Control for Frozen Policies
A Unified Sparse Attention via Multi-Granularity Compression
TimeOmni-VL: Unified Models for Time Series Understanding and Generation
Contrastive Diffusion Alignment: Learning Structured Latents for Controllable Generation
Provable Sample Efficiency of Curriculum Post-Training for Transformer Reasoning
Variational Routing: A Scalable Bayesian Framework for Calibrated Mixture-of-Experts Transformers
OmniSapiens: A Foundation Model for Social Behavior Processing via Heterogeneity-Aware Relative Policy Optimization
VIP: Visual-guided Prompt Evolution for Efficient Dense Vision-Language Inference
Collaborative Disagreement Resolution for Scalable Oversight
Turning Stale Gradients into Stable Gradients: Coherent Coordinate Descent with Implicit Landscape Smoothing for Lightweight Zeroth-Order Optimization
Model-Preserving Adaptive Rounding
On the Epistemic Uncertainty of Overparametrized Neural Networks
Position: AI Evaluations Should be Grounded on a Theory of Capability
Whom to Query for What: Adaptive Group Elicitation via Multi-Turn LLM Interactions
Flow Sampling : Learning to Sample from Unnormalized Densities via Denoising Conditional Processes
Causal Fine-Tuning under Latent Confounded Shift
Benchmarking at the Edge of Comprehension
Open-World LLM Logical Reasoning
Counterfactual Residual Data Augmentation for Regression
From Correspondence to Actions: Human-Like Multi-Image Spatial Reasoning in Multi-modal Large Language Models
Rethinking Pretraining Data Detection for LLMs: From Local to Global
SmartThinker: Progressive Chain-of-Thought Length Calibration for Efficient Large Language Model Reasoning
Differentially Private Preference Data Synthesis for Large Language Model Alignment
Phase-Type Variational Autoencoders for Heavy-Tailed Data
ReGen: Hierarchical Multi-Prompt Representation Generation for Efficient Waveform Diffusion Models
Calibrating Conservatism for Scalable Oversight
State-Dependent Safety Failures in Multi-Turn Language Model Interaction
Quantifying the Salience of Geo-Cultural Values for Pluralistic Safety Alignment
MentisOculi: Revealing the Limits of Reasoning with Mental Imagery
When Benign Inputs Lead to Severe Harms: Eliciting Unsafe Unintended Behaviors of Computer-Use Agents
Same Question, Different Lies: Cross-Context Consistency (C³) for Black-Box Sandbagging Detection
Multimodal Function Vectors for Visual Relations
DRPBench: Evaluating LLMs in Concurrent Code Comprehension via Fine-grained Data Race Prediction
FIRE: Learning to Navigate and Act on Real-World Files via Stateful Reinforcement Learning
IntentRL: Training Proactive User-intent Agents for Open-ended Deep Research via Reinforcement Learning
Spatial-Aware Reduction Framework: Towards Efficient and Faithful Visual State Space Models
Stabilizing PPO via Latent-Space Regularization and KDE-Driven Exploration
Multipole Semantic Attention: A Fast Approximation of Softmax Attention for Pretraining
How Transformers Represent Hierarchies: A Local-to-Global Mechanism
Approximate Equivariance via Projection-Based Regularisation
Test-Time Training with KV Binding Is Secretly Linear Attention
Temporal Self-Rewarding Language Models: Decoupling Chosen-Rejected via Past-Future
Rethinking Federated Prompt Learning for Medical Images: From Textual Tuning to Visual Manifold Anchoring
You Need Better Attention Priors
RMNP: Row-Momentum Normalized Preconditioning for Scalable Matrix-Based Optimization
How Hard Can It Be? Hardness-Aware Multi-Objective Unlearning
Stable-GFlowNet: Toward Diverse and Robust LLM Red-Teaming via Contrastive Trajectory Balance
Revisiting Pre-Propagation GNNs: Robust Diffusion Operators and Hidden-State Re-Propagation
ERGeoBench: A Comprehensive Benchmark for Embodied Reasoning and Geo-localization in Multimodal Large Language Models
Optimization with Access to Auxiliary Information
CoLA: Cross-Modal Low-rank Adaptation for Multimodal Downstream Tasks
Mitigating Label Shift in Tabular In-Context Learning via Test-Time Posterior Adjustment
Spatially-Adaptive Gradient Re-parameterization for 3D Large Kernel Optimization
Position: AI Evaluation Should Work With Humans
SonicMaster: Towards Controllable All-in-One Music Restoration and Mastering
When AI Agents Compete for Jobs: Strategic Capabilities and Economic Dynamics of AI Labour Markets
MEDA: Medical-Oriented Activation Editing for Hallucination Mitigation in Medical Large Vision-Language Model
Automatic Construction of Clinical Scoring Systems with LLM Agents
Efficient Hallucination Detection for LLMs Using Uncertainty-Aware Attention Heads
Improving Backward Conformal Prediction via Non-Conformity Score Transformation
Grounded in Reality: Learning and Deploying Proactive LLM from Offline Logs
From Observations to States: Latent Time Series Forecasting
Understanding the Parameter Space Geometry of Transformers Encoding Boolean Functions
Deformba: Vision State Space Model with Adaptive State Fusion
Riemannian stochastic optimization for sufficient dimension reduction
SemanticNVS: Improving Semantic Scene Understanding in Generative Novel View Synthesis
Revisiting Spectral Representations in Generative Diffusion Models
Modeling Temporal scRNA-seq Data with Latent Gaussian Process and Optimal Transport
SE(3)-Equivariant Flow Matching with Gaussian Process Priors for Geometric Trajectory Prediction
Geometry-Aware Tabular Diffusion
NeuroMamba: A Universal Spatiotemporal Module for Robust Perception in Degraded Sensory Streams
XR-1: Towards Versatile Vision-Language-Action Models via Learning Unified Vision-Motion Representations
Towards On-Policy SFT: Distribution Discriminant Theory and its Applications in LLM Training
Efficient Diffusion LLMs via Temporal-Spatial Parallel Decoding and Confidence Extrapolation
Video-in-the-Loop: Span-Grounded Long Video QA with Interleaved Reasoning
Decomposed On-Policy Distillation for Vision-Language Reasoning: Steering Gradients for Visual Grounding
LaST$_{0}$: Latent Spatio-Temporal Chain-of-Thought for Robotic Vision-Language-Action Model
Iterated Population Based Training with Task-Agnostic Restarts
Neural Dispersion on Graphs
Riemannian Neural Optimal Transport
SoftBinary Coding: A New Information-Theoretic Paradigm for Neural Compression via Fast Channel Simulation
LIVE: Long-horizon Interactive Video World Modeling
FastSESR: Fast Scene-level Explicit Surface Reconstruction
SGMD: Score Gradient Matching Distillation for Few-Step Video Diffusion Distillation
Temporal-aware Flow Matching for Video Generation with Temporally Coherent Motion
GraphP-FL: Personalized Federated Graph Learning via Dynamic Structure Awareness and Fisher Information Elastic Alignment
Log-Normal Multiplicative Dynamics for Stable Low-Precision Deep Learning
A Narrowing Geometry in Contaminated Reasoning
Rethinking Efficient Graph Coarsening via a Non-Selfishness Principle
Anchor-guided Hypergraph Condensation with Dual-level Discrimination
Nonconvex Low-Rank Tensor Representation with Deep Priors for Multiview Subspace Clustering
Alternating Reinforcement Learning for Rubric-Based Reward Modeling in Non-Verifiable LLM Post-Training
Turning Adaptation into Assets: Cross-Domain Bridging for Online Vision-Language Navigation
GraphFlow: A Graph-Based Workflow Management for Efficient LLM-Agent Serving
Expanding the Capabilities of Reinforcement Learning via Text Feedback
InnoEval: On Research Idea Evaluation as a Knowledge-Grounded, Multi-Perspective Reasoning Problem
SWE-MiniSandbox: Container-Free Reinforcement Learning for Building Software Engineering Agents
Breaking Manifold Continuity: Vector Quantized Modeling for Real-Centric Deepfake Detection
Rule2DRC: Benchmarking LLM Agents for DRC Script Synthesis with Execution-Guided Test Generation
Conditional Quantile Adjusted Conformal Prediction for Time Series
Towards Disentangled Preference Optimization Dynamics: Suppress the Loser, Preserve the Winner
RaBitQCache: Rotated Binary Quantization for KVCache in Long Context LLM Inference
EpiCache: Episodic KV Cache Management for Long-Term Conversation on Resource-Constrained Environments
S-Quant: Rethinking Weight Quantization with Seed-Based Generation
Fair Transit Stop Placement: A Clustering Perspective and Beyond
Can LLM Agents Stick to the Script? Modeling Commitment in Interactive Narratives
Scaling Vision Transformers for Functional MRI with Flat Maps
Anchored Policy Optimization: Mitigating Exploration Collapse via Support-Constrained Rectification
Utility-Diversity Aware Online Batch Selection for LLM Supervised Fine-tuning
BandPO: Bridging Trust Regions and Ratio Clipping via Probability-Aware Bounds for LLM Reinforcement Learning
Position: Regulating Algorithms Is Not Enough. A Study of Content Discovery in Online Platforms
PostTrainBench: Can LLM Agents Automate LLM Post-Training?
Navigating Massive Visual Context in Retrieval-Augmented Generation via Multimodal Memory Graph
Discrete Diffusion with Physical Mass Constraints for \emph{De Novo} Peptide Sequencing
Attn-QAT: 4-Bit Attention With Quantization-Aware Training
Large-Scale Molecular Dynamics Simulations: Direct Interatomic Modeling with Dilated Message Passing
Controllable Molecule Generation via Sparse Representation Editing: An Interpretability-Driven Perspective
Representation Learning for Equivariant Inference with Guarantees
HybridFlow: Resource-Adaptive Subtask Routing for Efficient Edge-Cloud LLM Inference
Global Credit Assignment via Dynamical Criticality
What Really Improves Mathematical Reasoning: Structured Reasoning Signals Beyond Pure Code
DMCO: Budget-Aware Co-Optimization of Data Cleaning and AutoML
HyperMLP: An Integrated Perspective for Sequence Modeling
Logit-Attention Divergence: Mitigating Position Bias in Multi-Image Retrieval via Attention-Guided Calibration
Names Don’t Matter: Symbol-Invariant Transformer for Open-Vocabulary Learning
Know Thyself, Know Thy User: Intrinsic Dual-Perspective Reasoning for Role-Playing LLMs
Beyond Perplexity: UTF-8 Validity in Byte-aware Language Models
Conformal Thinking: Risk Control for Reasoning on a Compute Budget
Alignment-Guided Score Matching for Text-to-Image Alignment in Diffusion Models
AutoWebWorld: Synthesizing Infinite Verifiable Web Environments via Finite State Machines
AOrchestra: Automating Sub-Agent Creation for Agentic Orchestration
Pushing Forward Pareto Frontiers of Proactive Agents with Behavioral Agentic Optimization
Offline Two-Player Zero-Sum Markov Games with KL Regularization
Zero-source LLM Hallucination Detection with Human-like Criteria Probing
Towards Sub-second Biological Foundation Model Infrastructure: A Quantized Consistency Diffusion Framework for Molecular Docking
Symbol-Equivariant Recurrent Reasoning Models
Optimizing Inference-Time Compute for Medical Reasoning via Uncertainty Quantification
Expectation Alignment of Language Models for Real-World User Expectations
Learning Cardiac Latent Representations in Vectorcardiogram Space
Activation with Intrinsic-Extrinsic Consensus
GRPO is Secretly a Process Reward Model
Controlling the Risk of Corrupted Contexts for Language Models via Early-Exiting
PersistBench: When Should Long-Term Memories Be Forgotten by LLMs?
Revisiting Coding-Based Approaches to Overcome the Curse of Dimensionality in Learning-Based Watermarking
Intra-Modal Neighbors Never Lie: Rectifying Inter-Modal Noisy Correspondence via Graph-Based Intra-Modal Reasoning
Stable Spectral Copula Alignment for Robust Multimodal Learning
DeCoDe: Decoupling Binding Position and Molecular Conformation in 3D Ligand Diffusion for Structure-Based Drug Design
Submodular Optimization for Minimal Augmentation in Robust Language Model Alignment
Interpretable Neural ODEs for Gene Regulatory Network Discovery under Perturbations
Temperature Scaling in Discrete Sequence (Language) Models
Multi-Objective Bayesian Optimization via Adaptive $\varepsilon$-Constraint Decomposition
Scam2Prompt: A Scalable Framework for Auditing Malicious Scam Endpoints in Production LLMs
Effects of Structural Reward Shaping on Biophysical Properties in RL-Trained Plasmid Generators
Where Concept Erasure Should Occur: Concept–Layer Alignment in Text-to-Video Diffusion Models
Robust Vision-Language Models via Manifold-Adversarial Adapters
Instruction Lens Score: Your Instruction Contributes a Powerful Object Hallucination Detector for Multimodal Large Language Models
MAFE: Enabling Equitable Algorithm Design in Multi-Agent Multi-Stage Decision-Making Systems
On the Adversarial Robustness of Large Vision-Language Models under Visual Token Compression
ArcDAE: Asymmetric Rectified Contrastive Diffusion Autoencoder for Unified Representation Learning
Position: Unlabeled ≠ No Human Supervision in Visual Learning
Heterogeneity-Aware Knowledge Sharing for Graph Federated Learning
With Argus Eyes: Assessing Retrieval Gaps via Uncertainty Scoring to Detect and Remedy Retrieval Blind Spots
Optimizing Few-Step Generation with Adaptive Matching Distillation
Exploring Data-Free LoRA Transferability for Video Diffusion Models
TurboGS: Accelerating 3D Gaussian Splatting via Error-Guided Sparse Pixel Sampling and Optimization
DECOR: Learning to Decompose and Collaborate in Deep Search via Multi-Agent Reinforcement Learning
Towards Foundation Models for Zero-Shot Time Series Anomaly Detection: Leveraging Synthetic Data and Relative Context Discrepancy
Wasserstein Geometry-Aware Adaptive Control via Meta-Learning
Subliminal Effects in Your Data: A General Mechanism via Log-Linearity
TimeGuard: Channel-wise Pool Training for Backdoor Defense in Time Series Forecasting
AVTrack: Audio-Visual Tracking in Human-centric Complex Scenes
Stabilizing Recurrent Dynamics for Test-Time Scalable Latent Reasoning in Looped Language Models
How Powerful are LLMs in Generating Formal Program Specifications?
Quantitative Estimation of Target Task Performance from Unsupervised Pretext Task in Semi/Self-Supervised Learning
Beyond Detection: A Structure-Aware Framework for Scene Text Tracking
Lifting Traces to Logic: Programmatic Skill Induction with Neuro-Symbolic Learning for Long-Horizon Agentic Tasks
DRFusion: Drift-Resilient Temporally Consistent Infrared–Visible Video Fusion
Exact and Approximate Algorithms for Polytree Learning
EAGer: Entropy-Aware GEneRation for Adaptive Inference-Time Scaling
EMFormer: Efficient Multi-Scale Transformer for Accumulative Context Weather Forecasting
HALO: A Unified Vision-Language-Action Model for Embodied Multimodal Chain-of-Thought Reasoning
Towards Diffeomorphism-Equivariant Neural Networks via Canonicalization
Geometric Collapse: When Vision Models Fail to Verify Physical Causality
WorldComp2D: Spatio-semantic Representations of Object Identity and Location from Local Views
Sample from What You See: Visuomotor Policy Learning via Diffusion Bridge with Observation-Embedded Stochastic Differential Equation
WBMM: Windowed Batch Matrix Multiplication for Efficient Large Receptive Field Convolution
EPS3D: End-to-End Feed-Forward 3D Panoptic Segmentation
Understand and Accelerate Memory Processing Pipeline for Large Language Model Inference
Lagrangian Perturbation Diffusion Steering: Latent Reinforcement Learning for Generative Policies
Native Spatio-Temporal 4D Variational Autoencoder
WildActor: Unconstrained Identity-Preserving Video Generation
AgentXRay: White-Boxing Agentic Systems via Workflow Reconstruction
Derivative Informed Learning of Exchange-Correlation Functionals
ARLArena: A Unified Framework for Stable Agentic Reinforcement Learning
GenAlign: Towards Unified Alignment Framework of MLLMs via Generative Reward Model
MADA-Attack: Transferable Multi-modal Attention Distraction Adversarial Attack against Vision Language Models
Listening Through the Noise: Cauchy-Driven Diffusion Bridges for Robust Gastrointestinal Auscultation and Clinical Benchmarking
Pianist Transformer: Towards Expressive Piano Performance Rendering via Scalable Self-Supervised Pre-Training
Seizure-Semiology-Suite($S^3$): A Clinically Multimodal Dataset, Benchmark, and Models for Seizure Semiology Understanding
Not All Invariants Are Equal: Curating Training Data to Accelerate Program Verification with SLMs
From Token to Token Pair: Efficient Prompt Compression for Large Language Models in Clinical Prediction
Rethinking Serialization in Linear 3D Vision: Decoupling Anisotropic Geometry from Isotropic Semantics
Neural Attention Search Linear: Towards Adaptive Token-Level Hybrid Attention Models
Long-Horizon Model-Based Offline Reinforcement Learning Without Explicit Conservatism
Scaling up Multi-Turn Off-Policy RL and Multi-Agent Tree Search for LLM Step-Provers
SurvDiff: A Diffusion Model for Generating Synthetic Data in Survival Analysis
MixReasoning: Switching Modes to Think
Learning Sparse Visual Representations via Spatial-Semantic Factorization
RNA-FM: Flow-Matching Generative Model for Genome-wide RNA-Seq Prediction
FunCQNet: A Functional Censored Quantile Neural Network for Predicting Long-Term Post-Transplant Kidney Survival
Many Needles in a Haystack: Active Hit Discovery for Perturbation Experiments
The First Drop of Ink: Nonlinear Impact of Misleading Information in Long-Context Reasoning
SWE-Bench Pro: Can AI Agents Solve Long-Horizon Software Engineering Tasks?
AuTAgent: A Reinforcement Learning Framework for Tool-Augmented Audio Reasoning
Reduction of Probabilistic Chemical Reaction Networks
The Silent Thought: Modeling Internal Cognition in Full-Duplex Spoken Dialogue Models via Latent Reasoning
A Semantically Consistent Dataset for Data-Efficient Query-Based Universal Sound Separation
Expected Return Causes Outcome-Level Mode Collapse in Reinforcement Learning and How to Fix It with Inverse Probability Scaling
Training LLM Agents to Empower Humans
DeFacto: Counterfactual Thinking with Images for Enforcing Evidence-Grounded and Faithful Reasoning
Position: Evaluating LLMs in Finance Requires Explicit Bias Consideration
On the "Induction Bias" in Sequence Models
Position: Large Language Models Should Learn Personalized Rather Than Aggregated Human Preferences
Characterizing the Predictive Impact of Modalities with Supervised Latent-Variable Modeling
Efficient Distributionally Robust Assortment Optimization in MNL Bandits
Semantic-Enriched Latent Visual Reasoning
What Does Vision Tool-Use Reinforcement Learning Really Learn? Disentangling Tool-Induced and Intrinsic Effects for Crop-and-Zoom
Quantile-Free Uncertainty Quantification in Graph Neural Networks
AutoMoT: A Unified Vision-Language-Action Model with Asynchronous Mixture -of-Transformers for End-to-End Autonomous Driving
FairRARI: A Plug and Play Framework for Fairness-Aware PageRank
Transport or Discard: Robust Unbalanced Optimal Transport for Cross-Domain Policy Adaptation
When Single Answer Is Not Enough: Rethinking Single-Step Retrosynthesis Benchmarks for LLMs
Row-Stochastic Matrices Can Provably Outperform Doubly Stochastic Matrices in Decentralized Learning
Finite-time Convergence Analysis of Actor-Critic with Evolving Reward
Not All Frequencies Are Equal: Energy-Adaptive Diffusion for Time Series Forecasting
Position: Agentic Safety is an Epistemic Property, Not a Behavioral One
Conformal Risk-Averse Decision Making with Action Conditional Guarantee
ZeroDiff: Zero-Shot Time Series Reconstruction via Informed-Prior Diffusion
Metis: Learning to Jailbreak LLMs via Self-Evolving Metacognitive Policy Optimization
Positional Encoding for Spiking Transformers
REALISTA: Realistic Latent Adversarial Attacks that Elicit LLM Hallucinations
ADHD Disease Detection Based on Short- and Long-Term Brain Function Encoding and Memory Graph Network
Learning to Theorize the World from Observation
Probabilistic Bisection Algorithm Provably Achieves Exponential Convergence
JADAI: Jointly Amortizing Adaptive Design and Bayesian Inference
Learning Fingerprints for Medical Time Series with Redundancy-Constrained Information Maximization
Bayesian Meta-Learning with Expert Feedback for Task-Shift Adaptation through Causal Embeddings
Copyright-Bench: Agentic Evaluation of Copyright Law Compliance
TeamWork: Multivariate Time Series Anomaly Detection via Asymmetric Role-aware Channel Modeling
Safety Game: Inference-Time Alignment of Black-Box LLMs via Constrained Optimization
AutoVSR: Automatic Visual-to-Symbolic Reasoning for Symbolic Expression Generation from Circuit Schematic
Beyond Rewards in RL for Cyber Defence
RulePlanner: All-in-One Reinforcement Learner for Unifying Design Rules in 3D Floorplanning
Physically-Guided Data-Space Rectified Flow for Precipitation Nowcasting
Large-Scale Notification Dispatch with Bundle Treatments and Multi-Outcome Uplift Optimization
SARL: Structure-Aligned Reinforcement Learning for Bridging the Perception-Action Gap in Airspace
ProRL: Effective Reinforcement Learning for Proactive Recommendation via Rectified Policy Gradient Estimation
BiTrajDiff: Bidirectional Trajectory Generation with Diffusion Models for Offline Reinforcement Learning
SEAgent: Self-Evolving Computer Use Agent with Autonomous Learning from Experience
Provably Convergent Actor-Critic in Risk-averse MARL
Towards Trustworthy and Identifiable Virtual Face Generation
Online Rubrics Elicitation from Pairwise Comparisons
Position: Generative Models Erode Temporal Learning Through Market Selection
Flexibility-Aware Geometric Latent Diffusion for Full-Atom Peptide Design
Position: Prompts for Public-Sector LLMs Should Be Governed as Commons
Learning Latent Action World Models in the Wild
Beyond Static Pipelines: Learning Dynamic Workflows for Text-to-SQL
Position: Why a Dynamical Systems Perspective is Needed to Advance Time Series Modeling
B-Spar: Bayesian Sparse-Reward Modeling for RL-based Image Editing
OpenGPT-4o-Image: A Comprehensive Dataset for Advanced Image Generation and Editing
Spurious Rewards Paradox: Mechanistically Understanding How RLVR Activates Memorization Shortcuts in LLMs
Beyond Instance-Level Self-Supervision in 3D Multi-Modal Medical Imaging
Orthogonal Hierarchical Decomposition for Structure-Aware Table Understanding with Large Language Models
Episodic Memory-Guided Controllable Experience Synthesis for Reinforcement Learning
Relational In-Context Learning via Synthetic Pre-training with Structural Prior
GRASP: Graph Reasoning via Agentic Solving and Probing of LLMs
Position: Multiple Definitions & Unrealistic Assumptions of Model Collapse Distract from Real World Threats
Position: Quantum Program Generation Must Prioritize Validity Over Probabilistic Scaling
FlexiFlow: decomposable flow matching for generation of flexible molecular ensemble
The Double-Edged Nature of the Rashomon Set for Trustworthy Machine Learning
Seeing the Unseen: Physics-as-Representation for Generalizable Gaze Perception
Noise as a Natural Regularizer in Markov Decision Processes: Connecting Environmental Stochasticity and Policy Simplicity
Expo-GS: Exposure-Aware Signed Distance Function in Gaussian Splatting for High Dynamic Range
Spike Camera Autofocus via Frequency-Domain Spectral-Centroid Migration
Towards Trustworthy Video Anomaly Understanding: A Class-Guided Chain-of-Evaluation Metric and An Anomaly-focused Meta-Benchmark
SC-FAGC: Size Constrained Fast Anchor-based Graph Clustering
Retro-Expert: Collaborative Reasoning for Interpretable Retrosynthesis
EquiCAD: A Geometric Equivariant Neural Network for 3D Shape Classification
Plug-and-Play Guidance for Discrete Diffusion Models via Gradient-Informed Logit Correction
Reasoning Is Not Free: Robust Adaptive Cost-Efficient Routing for LLM-as-a-Judge
Overcoming the Modality Gap in Context-Aided Forecasting
Efficient Transformer Attention for SNNs via Hadamard Simplification
ECHO: Entropy-Confidence Hybrid Optimization for Test-Time Reinforcement Learning
Persona-Pruner: Sculpting Lightweight Models for Role-Playing
ExpertWeaver: Unlocking the Inherent MoE in Dense LLMs with GLU Activation Patterns
ECO: Quantized Training without Full-Precision Master Weights
Hyperbolic Multimodal Continual Learning
Contribution Weights: A Geometrical Analysis of Self-Attention Transformers
The Efficiency Gap in Byte Modeling
Investigating Continual Pretraining in Large Language Models: Insights and Implications
Position: Prompting Intent Should Be Audited in LLM-Assisted Peer Review
Graph Neural Dynamics via Learned Energy and Tangential Flows
Barriers to Counterfactual Credit Attribution for Autoregressive Models
The Expressivity Limits of Transformers
The Optimal Sample Complexity of Linear Contracts
Who Transfers Safety? Identifying and Targeting Cross-Lingual Shared Safety Neurons
The Interplay Between Interpolation and Aggregation in Regression: Optimal Sample Complexity
A Unified Framework for Deep Hypergraph Clustering Beyond Homophily
Task-Awareness Improves LLM Generations and Uncertainty
What Characterizes Effective Reasoning? Revisiting Length, Review, and Structure of CoT
Efficient RL Training for LLMs with Experience Replay
Teaching Models to Teach Themselves: Reasoning at the Edge of Learnability
Theoretical Guarantees for One-Shot Magnitude Pruning and Compute-Adaptive Early Exit
Revisiting Zeroth-Order Hessian Approximation: A Single-Step Policy Optimization Lens
When Tabular Foundation Models Meet Strategic Tabular Data: A Prior Alignment Approach
Provably Data-driven Lagrangian Relaxation for Mixed Integer Linear Programming
Selective Disclosure Watermarking for Large Language Models
FeRA: Frequency-Energy Constrained Routing for Effective Diffusion Adaptation Fine-Tuning
Particles Don’t Care About Z: Towards Scaling Entropy Estimation of Unnormalized Densities
Mirror Mean-Field Langevin Dynamics
Perceptual Flow Network for Visually Grounded Reasoning
Learning Discrete Diffusion on Graphs via Free-Energy Gradient Flows
New Bounds for Kernel Sums via Fast Spherical Embeddings
Leveraging Gauge Freedom for Learning Non-Gradient Population Dynamics of Stochastic Systems
dnaHNet: A Scalable and Hierarchical Foundation Model for Genomic Sequence Learning
Online Conformal Prediction via Universal Portfolio Algorithms
Search Space Synthesis for Parametric Functions
Causal Modeling of Selection in Evolution
Diffusion Bridge or Flow Matching? A Unifying Framework and Comparative Analysis
CSOR: Coreset Selection for Object Re-identification via Class Pruning
ParEVO: Synthesizing Code for Irregular Data: High-Performance Parallelism through Agentic Evolution
CooT: Learning to Coordinate In-Context with Coordination Transformers
Rapid Poison: Practical Poisoning Attacks Against the Rapid Response Framework
PRISM: Learning Realistic Depth via Physics-Grounded Noise Disentanglement with Semantic-Geometric Collaboration
Estimating Tail Risks in Language Model Output Distributions
Reasoning to Edit: Hypothetical Instruction-Based Image Editing with Visual Reasoning
Estimating the Empowerment of Language Model Agents
QiMeng-LibBench: Benchmarking LLM Agents for Library-Scale Cross-Architecture Migration
Rethinking Video Generation Model for the Embodied World
Beyond Pixel Histories: World Models with Persistent 3D State
Gradient Flow Sampler-based Distributionally Robust Optimization
LEMUR: Learned Multi-Vector Retrieval
Improved Stochastic Optimization of LogSumExp
FedRot-LoRA: Mitigating Rotational Misalignment in Federated LoRA
PhysForge: Generating Physics-Grounded 3D Assets for Interactive Virtual World
Beyond Hamming: Query-Aware Decoding of Binary Cosine Sketches
Search-R2: Enhancing Search-Integrated Reasoning via Actor-Refiner Collaboration
The benefits of full data shuffle, now with optimal I/O cost: $k$-wise independence and matrix transposition to the rescue
Are Your Agents Upward Deceivers?
MoCL: Metabolic Optimization for Curvature-Aware Continual Learning
Dynamic Optimizations of LLM Ensembles with Two-Stage Reinforcement Learning Agents
DiLA: Disentangled Latent Action World Models
Shapley Neuron Values for Continual Learning: Which Neurons Matter Most?
Feature Collapse Under Corruption: An Entropy Perspective on Robust Neural Networks
Structure Abstraction and Generalization in a Hippocampal-Entorhinal Inspired World Model
Mixing Expertise with Confidence: A Mixture of Experts Framework for Robust Multi-Modal Continual Learning
CARD: Coarse-to-fine Autoregressive Modeling with Radix-based Decomposition for Transferable Free Energy Estimation
Segment Anything with Robust Uncertainty-Accuracy Correlation
DomED: Redesigning Ensemble Distillation for Domain Generalization
Attributed Network Alignment: Statistical Limits and Efficient Algorithm
Lightweight Federated Incremental Learning via Decoupled Replay
Beyond Single Embedding: Modeling User Preferences as Distribution in Federated Recommendation
RC-FCL: Combating Asynchronous Concept Drift in Federated Continual Learning via Retrospective Calibration
Approximate Nearest Neighbor Search for Modern AI: A Projection-Augmented Graph Approach
Tackling Fake Forgetting through Uncertainty Quantification
ICR-RL: Deep Reinforcement Learning via In-Context-Regression
Operator Splitting with Hamilton-Jacobi-based Proximals
Learning Permutation from Structure Without Supervision
Improved Dynamic Algorithm for Non-monotone Submodular Maximization under Cardinality Constraint
Exploring Nonlinear Pathway in Parameter Space for Machine Unlearning
Watermarking Graph Neural Networks via Explanations for Ownership Protection
UniFLoW: Universal Multi-Modal Federated LoRA Fine-Tuning Framework with Analytical Aggregation
Understanding SAM through Minimax Perspective
The Fairness Hierarchy: A viewpoint from causal inference
Near-Optimal and Efficient First-Order Algorithm for Multi-Task Learning with Shared Linear Representation
Landmark-Guided Policy Optimization for Multi-Objective Language Model Selection
OVLR: Efficient, Scalable, and Robust Training via Output-Level Variance-Reduced Likelihood Ratio
An Embarrassingly Simple Way to Optimize Orthogonal Matrices at Scale
OPT-Engine: Benchmarking the Limits of LLMs in Optimization Modeling via Complexity Scaling
EnerGS: Energy-Based Gaussian Splatting under Partial Geometric Priors
Mirror Descent Under Generalized Smoothness
SurrogateSHAP: Training-Free Contributor Attribution for Text-to-Image (T2I) Models
Exploration Hacking: Can LLMs Learn to Resist RL Training?
MaMa: A Game-Theoretic Approach for Designing Safe Agentic Systems
COPF: An Online Framework for Deployment-Stable Counterfactual Fairness in Evolving Graphs
IACW: Intent-Aware Controllable Watermarking for Scalable Authorial Intent Attribution
Demystifying the Optimal Fair Classifier in Multi-Class Classification
Sparse Tokens Suffice: Jailbreaking Audio Language Models via Token-Aware Gradient Optimization
RoboMME: Benchmarking and Understanding Memory for Robotic Generalist Policies
Parallel-Probe: Towards Efficient Parallel Thinking via 2D Probing
Preconditioned DeltaNet: Curvature-aware Sequence Modeling for Linear Recurrences
Repositioning the Subject within Image
Prompt Reinjection: Alleviating Prompt Forgetting in Multimodal Diffusion Transformers
NanoQuant: Efficient Sub-1-Bit Quantization of Large Language Models
SIGMA-PPG: Statistical-prior Informed Generative Masking Architecture for PPG Foundation Model
Executable Agentic Memory for GUI Agent
FedHPro: Federated Hyper-Prototype Learning via Gradient Matching
Eliminating Solution Bias in Differentially Private Optimization
Fast and Expressive Multi-Byte Prediction with Probabilistic Circuits
Learning GUI Grounding with Spatial Reasoning from Visual Feedback
OSNIP: Balancing the Privacy-Utility-Efficiency Trilemma in LLM Inference via Obfuscated Semantic Null Space
Shuffling-Aware Optimization for Private Vector Mean Estimation
No Data? No Problem: Robust Vision-Tabular Learning with Missing Values
Differentially Private Synthetic Data via APIs 4: Tabular Data
Multi-Scale Wavelet Transformers for Operator Learning of Dynamical Systems
ACTG-ARL: Differentially Private Conditional Text Generation with RL-Boosted Control
Understanding and Mitigating Token-Pruning-Induced Vulnerabilities in VLMs
Machine Learning Hamiltonians are Accurate Energy-Force Predictors
Position: AI Leaderboards Are Underserving the Global South: A Case Study from India
Internalizing Safety Understanding in Large Reasoning Models via Verification
Toward Training Superintelligent Software Agents through Self-Play SWE-RL
PAC-Bayesian Reinforcement Learning Trains Generalizable Policies
Optimized Deferral for Imbalanced Settings
Keep It in Mind: User Centric Continual Spatial Intelligence Reasoning in Egocentric Video Streams
MM-DeepResearch: A Simple and Effective Multimodal Agentic Search Baseline
Reusing Trajectories in Policy Gradients Enables Fast Convergence
AnyCanvas: Potential Field Guidance for Training-Free Spatial Control in Text-to-Image Diffusion
Reference-Free Meta-Learning for Generalized Implicit Neural Representation in Efficient MRI Reconstruction
Revisiting the Role of Pretrained Weights in Model Merging: On Near-Optimality within the Core Subspace
RSF-GLLM: Bridging the Semantic Gap in Multi-Hop Knowledge Graph QA via Recurrent Soft-Flow and Decoupled LLM Generation
WorldMirror: Universal 3D World Reconstruction with Any-Prior Prompting
GTPO and GRPO-S: Token and Sequence-Level Reward Shaping with Policy Entropy
KODA: Contrastive Representation Comparison and Alignment for Vision-Language Foundation Models
Asymmetric Contrastive Objectives for Efficient Phenotypic Screening
Decentralized Bandits without Global Clock for Dynamic Matching Market
Harnessing Non-Adversarial Robustness in Large Language Models
nD-RoPE: A Generalized RoPE for n-Dimensional Position Embedding
GHOST: Unmasking Phantom States in Mamba2 via Grouped Hidden-state Output-aware Selection & Truncation
LC-QAT: Data-Efficient 2-Bit QAT for LLMs via Linear-Constrained Vector Quantization
Semantic Impact–Driven Visual Scheduling in Vision-Language Models
Position: Predicting AI’s Impact on Labor Is a Core Machine Learning Problem
VGGT-Motion: Motion-Aware Calibration-Free Monocular SLAM for Long-Range Consistency
Multimodal Meta-Verifier with Explicit Structured Recalibration
Quantifying Error Propagation and Model Collapse in Diffusion Models
STAR: Rethinking MoE Routing as Structure-Aware Subspace Learning
Harnessing Reasoning Trajectories for Hallucination Detection via Answer-agreement Representation Shaping
Q-Delta: Beyond Key–Value Associative State Evolution
The Implicit Bias of Steepest Descent with Mini-batch Stochastic Gradient
Scaling Laws for Precision in High-Dimensional Linear Regression
V-LynX: Token Interface Alignment for Video+X LLMs
Focusing Where Vision Matters: Selective Training for Large Vision Language Models via Visual Information Gain
SPARe: Stacked Parallelism with Adaptive Reordering for Fault-Tolerant LLM Pretraining Systems with 100k+ GPUs
Consistent Zero-Shot Imitation with Contrastive Goal Inference
Calibrating Generative Models to Distributional Constraints
HIVE-3D: Hierarchical Voxel Enhancement for High-Quality 3D Scene Generation
Autoregression with Self-Token Prediction
Interpreting and Steering State-Space Models via Activation Subspace Bottlenecks
Supervised Classification Heads as Semantic Prototypes: Unlocking Vision-Language Alignment via Weight Recycling
Variational Bayesian Flow Network for Graph Generation
MuLoCo: Muon is a Practical Inner Optimizer for DiLoCo
FunPhase: A Periodic Functional Autoencoder for Motion Generation via Phase Manifolds
VideoGPA: Distilling Geometry Priors for 3D-Consistent Video Generation
Learning $U$-Statistics with Active Inference
Pose-ICL: 3D-Aware In-Context Learning for Pose-Controllable Subject Customization
Safe Autoregressive Image Generation with Iterative Self-Improving Codebooks
Universal Multiclass Transductive Online Learning
Compression as Adaptation: Implicit Visual Representation with Diffusion Foundation Models
Active Continual Learning with Metaplastic Binary Bayesian Neural Networks
RevealLayer: Disentangling Hidden and Visible Layers via Occlusion-Aware Image Decomposition
Nonparametric Data Attribution for Diffusion Models
Learning to Rank from Incomplete Rankings
Learning, Solving and Optimizing PDEs with TensorGalerkin: an efficient high-performance Galerkin assembly algorithm
Beyond Model Base Retrieval: Weaving Knowledge to Master Fine-grained Neural Network Design
CONGA:Confidence-and-Gradient-Aware Learning Rate Schedule for Test Time Adaptation
H$^2$CL: Heterogeneity-Aware Hypergraph Contrastive Learning for Robust Representation Learning
Rethinking Graph Transformers as Graph Signal Denoisers: The Role of Block-Diagonal Priors
What Makes a Desired Graph for Relational Deep Learning?
SEMIR: Semantic Minor-Induced Representation Learning on Graphs for Visual Segmentation
Synergistic Space-Vision Processing for Predicate Inference
Dual-channel Dynamic Graph Neural Networks with Adaptive Adjacency Learning and Multi-scale Representation Fusion
Position: Adversarial ML for LLMs Is Not Making Any Progress
Grounding LLMs in Scientific Discovery via Embodied Actions
Position: LLMs can't jump
On the Expressive Power of GNNs to Solve Linear SDPs
Diversity Over Frequency: Rethinking Tool Use in Visual Chain-of-Thought Agents
Model Monotonicity in Autobidding Auctions: When Do Better Predictions Lead to Better Outcomes?
Mosaic: Unlocking Over 30$\times$ Context Length for Diffusion LLMs Inference via Global Memory Planning and Dynamic Peak Taming
SpatioLM: Towards General Physical Spatial Intelligence in Vision-Language Models
Conditional Clifford-Steerable CNNs for PDE Modeling
Graph Neural Networks Are Not Continuous Across Graph Resolutions
Identifiable Smooth Conjugacy Learning via Adversarial Orthogonality
Escaping Mode Collapse in LLM Generation via Geometric Regulation
$\mathbb{R}^{2k}$ is Theoretically Large Enough for Embedding-based Top-$k$ Retrieval
PhaseAlign: Complex Phase Alignment for Stable Open-Vocabulary Semantic Segmentation
Grokking Finite-Dimensional Algebra
Exploration-free Algorithms for Multi-group Mean Estimation
Certificates for Complex-Compatible Learned Cochain Laplacians
ASyMOB: Algebraic Symbolic Mathematical Operations Benchmark
One Bias After Another: Mechanistic Reward Shaping and Persistent Biases in Language Reward Models
TiME: Test-Time Mixture-of-Experts Routing via Asymmetric CO-Optimal Transport for Continual Test-Time Adaptation
When Diffusion Language Models Hesitate: Detecting and Correcting Visual Hallucinations via Confidence Fluctuation
UrbanMLLM: Joint Learning of Cross-view Imagery for Urban Understanding
The Label Horizon Paradox: Rethinking Supervision Targets in Financial Forecasting
From Extraction to Deduction: Resolving Functional Misalignment in RAG via a Collaborative Critic-Reasoner Framework
Unifying Value Alignment and Assignment in Cross-Domain Offline Reinforcement Learning with Heterogeneous Datasets
Credibility-Aware Weighting Federated Causal Discovery for Time Series
SciPredict: Can LLMs Predict the Outcomes of Scientific Experiments in Natural Sciences?
LiveNewsBench: Evaluating Web Search Agents with Freshly Curated News
Recursive Models for Long-Horizon Reasoning
When Search Goes Wrong: Red-Teaming Web-Augmented Large Language Models
TimeMRA: LLM-Empowered Time Series Forecasting via Multi-Scale Retrieval-Augmented Representations
Position: Certified Correctness in Neural Constraint Reasoning Requires Symbolic Integration
ParaTool: Shifting Tool Representations from Context to Parameters
KORE: Enhancing Knowledge Injection for Large Multimodal Models via Knowledge-Oriented Controls
Hugging Carbon: Quantifying the Training Carbon Emissions of AI Models at Scale
PESD-TSF: A Period-Aware and Explicit Structured Decomposition Framework for Long-Term Time Series Forecasting
Unbiased Dynamic Pruning for Efficient Group-Based Policy Optimization
PRISM: Gauge-Invariant Tangent-Space Differentially Private LoRA
Beyond Mode Collapse: Distribution Matching for Diverse Reasoning
Effective MoE-based LLM Compression by Exploiting Heterogeneous Inter-Group Experts Routing Frequency and Information Density
Closing the Loop: Universal Repository Representation with RPG-Encoder
L2G-NET: Local to Global Spectral Graph Neural Networks via Cauchy Factorizations
EvoClaw: Evaluating AI Agents on Continuous Software Evolution
Reasoning-preserved Efficient Distillation of Large Language Models via Activation-aware Initialization
Priority-Aware Shapley Value
Marrying Generative Model of Healthcare Events with Digital Twin of Social Determinants of Health for Disease Reasoning
Skill-Based Mixture-of-Experts: Adaptive Routing for Heterogeneous Reasoning via Inferred Skills
SAME: Stabilized Mixture-of-Experts for Multimodal Continual Instruction Tuning
Memory is Reconstructed, Not Retrieved: Graph Memory for LLM Agents
Calibrated Knowledge Aggregation in Bayesian Mixture-of-Experts for Continual VQA
Position: *Beyond Text* The Text-Centric Bias in Foundation Models Must Be Revisited for a Speech-First Future
TileQ: Efficient Low-Rank Quantization of Mixture-of-Experts with 2D Tiling
AlienLM: Alienization of Language for API-Boundary Privacy in Black-Box LLMs
FairGB: A Fair Granular-Ball Generation Method for Data Classification
Graph Alignment for Benchmarking Graph Neural Networks and Learning Positional Encodings
WUSH: Near-Optimal Adaptive Transforms for LLM Quantization
PointDiT: Pixel-Space Diffusion for Monocular Geometry Estimation
Shape of Thought: Progressive Object Assembly via Visual Chain-of-Thought
Configurable Reward Model for Balanced Safety Alignment
LERD: Latent Event-Relational Dynamics for Neurodegenerative Classification
iLoRA: Bayesian Low-Rank Adaptation with Latent Interaction Graphs for Microbiome Diagnosis
CORE: Context-Robust Remasking for Diffusion Language Models
Scaling Multi-Agent Environment Co-Design with Diffusion Models
Rationality Measurement and Theory for Reinforcement Learning Agents
PINNfluence: Interpreting PINNs through Influence Functions
Position: Assistive AI requires Personalized Specialists, not Generalists
Think-at-Hard: Selective Latent Iterations to Improve Reasoning Language Models
Escaping the Verifier: Learning to Reason via Demonstrations
Error Amplification Limits ANN-to-SNN Conversion in Continuous Control
Graph-Link: Bridging the Semantic-Structural Gap in Text-to-SQL via Constrained Subgraph Induction
From Content to Knowledge: Lightning Fast Long-Video Understanding with Neural Knowledge Representations
RECOVER: Reliable Detection of Unauthorized Data Usage in Text-to-Image Diffusion Models via Inversion Robustness
InstEmb: Instruction-Following Embeddings through Glimpses of the Future
Minibatch Optimal Transport and Perplexity Bound Estimation in Discrete Flow Matching
Look on Demand: A Cognitive Scheduling Framework for Visual Evidence Acquisition in Multimodal Reasoning
From Welfare to Utility: Generalized Objectives in Budget-Feasible Procurement
Distributed Stochastic $K$-Level Optimization Over Networks
AIR: Post-training Data Selection for Reasoning via Attention Head Influence
Approximation Preserving Coresets
EchoRL: Reinforcement Learning via Rollout Echoing
Causal Forcing: Autoregressive Diffusion Distillation Done Right for High-Quality Real-Time Interactive Video Generation
Provably Learning Attention with Queries
Decouple Searching from Training: Scaling Data Mixing via Model Merging for Large Language Model Pre-training
Synthesizing world models for bilevel planning
Darwinian Memory: A Training-Free Self-Regulating Memory System for GUI Agent Evolution
Can I Have Your Order? Monte-Carlo Tree Search for Slot Filling Ordering in Diffusion Language Models
Adaptive Node Feature Selection for Graph Neural Networks
No More, No Less: Least-Privilege Language Models
Correcting in Hindsight: Editing Past Key-Value States for Robust LLM Reasoning
Future Dynamic 3D Reconstruction: A 3D World Model with Disentangled Ego-Motion
Compute as Teacher: Turning Inference Compute Into Reference-Free Supervision
Diving into Kronecker Adapters: Component Design Matters
Bayesian Gated Non-Negative Contrastive Learning
Towards Reliable Marking and Verification of AI-Generated Text via Geometry-aware Sentence-level Watermarking
Hista and Numca: Estimate State Value Effectively for Large Language Model Reinforcement Learning
Sim2Reason: Solving Physics Olympiad via Reinforcement Learning on Physics Simulators
AtomWorld: A Benchmark for Evaluating Spatial Reasoning in Large Language Models on Material Structures
Adversarial Reinforcement Learning for Robust Diffusion Large Language Model Unlearning
ViewMask-1-to-3: Multi-View Consistent Image Generation via Multimodal Discrete Diffusion Models
Talk, Judge, Cooperate: Gossip-Driven Indirect Reciprocity in Self-Interested LLM Agents
Multilingual Safety Alignment via Representation-Space Separability
Sparks of Cooperative Reasoning: LLMs as Strategic Hanabi Agents
Attention Sinks in Diffusion Transformers: A Causal Analysis
ePC: Fast and Deep Predictive Coding in Digital Simulation
Lost in Context: Adressing Context Anxiety in Large Language Models
CompleteP for RL: Maintaining Feature Learning When Scaling Deep Reinforcement Learning
Second-Order Bilevel Optimization with Accelerated Convergence Rates
Position: Ideas Should be the Center of Machine Learning Research
Riemannian Networks over Full-Rank Correlation Matrices
WF-Bench: A Benchmark for Neural-Network WaveFunction Expressivity and Scaling Laws
Continuous Variable Hamiltonian Learning at Heisenberg Limit via Displacement-Random Unitary Transformation
``Someone Hid It!'': Query-Agnostic Black-Box Attacks on LLM-Based Retrieval
A Bayesian Approach to Quantify the Uncertainty of Human Ratings in a Single-Instance Multimodal Framework
Certified Robustness under Heterogeneous Perturbations via Hybrid Randomized Smoothing
CoRe: Collaborative Reasoning via Cross Teaching
UrbanFusion: Stochastic Multimodal Fusion for Contrastive Learning of Robust Spatial Representations
LLM Watermark Evasion via Bias Inversion
Hidden in Plain Sight -- Class Competition Focuses Attribution Maps
Quantifying the Uncertainty of Foundation Models with Singular Value Ensembles
Blending Supervised and Reinforcement Fine-Tuning with Prefix Sampling
Clustering in Deep Stochastic Transformers
EVMbench: Evaluating AI Agents on Smart Contract Security
GenDA: Generative Data Assimilation on Complex Urban Areas via Classifier-Free Diffusion Guidance
Position: Sycophancy is an Educational Safety Risk: Why LLM Tutors Need Sycophancy Benchmarks
Physics-Informed Pre-training on Efficient Electron-Density Images for Organic Material Property Prediction
Graph Rewiring based on Flow Alignment for Improving Fluid Simulation
Impact of Connectivity on Laplacian Representations in Reinforcement Learning
Mesh Based Simulations with Spatial and Temporal awareness
E2Former-V2: On-the-Fly Equivariant Attention with Linear Activation Memory
Corrected Samplers for Discrete Flow Models
Order Matters in Retrosynthesis: Structure-aware Generation via Reaction-Center-Guided Discrete Flow Matching
Data-driven Mixed Integer Optimization through Probabilistic Multi-variable Branching
This State Looks Like That: Self-Interpretable Reinforcement Learning Agents using Prototype Soft Actor-Critic
Beyond Distribution Estimation: Simplex Anchored Structural Inference Towards Universal Semi-Supervised Learning
The Heterogeneous Safety Impacts of Benign Multilingual Fine-Tuning
HiPhO: How Far Are (M)LLMs from Humans in the Latest High School Physics Olympiad Benchmark?
Beyond Token-level Supervision: Unlocking the Potential of Decoding-based Regression via Reinforcement Learning
Intrinsic Gradient Suppression for Label-Noise Prompt Tuning in Vision–Language Models
Fixed Aggregation Features Can Rival GNNs
Robustness of Mixtures of Experts to Feature Noise
Memory as Dynamics: Learning Reliability-Guided Predictive Models for Online Video Perception
Position: AI Must Become Planet-Centered, Not Human-Centered
Code2Video: A Code-centric Paradigm for Educational Video Creation
Dynamic Multimodal Evaluation via Knowledge-Enhanced Benchmark Evolution
Emergent Analogical Reasoning in Transformers
PVDepth: Panoramic Video Depth Estimation via Geometry-Aware Spatiotemporal Adaptation
Learning 3D-Gaussian Simulators from RGB Videos
Decoupling Skeleton and Flesh: Efficient Multimodal Table Reasoning with Disentangled Alignment and Structure-aware Guidance
Code2Worlds: Empowering Coding LLMs for 4D World Generation
Bipartite Graph Attention-based Clustering for Large-scale scRNA-seq Data
Just Noticeable Difference Modeling for Deep Visual Features
Conflict-Aware Adaptive Alignment for LLM Hallucination Mitigation
Contrastive Geometric Learning Unlocks Unified Structure- and Ligand-Based Drug Design
Prototype Transformer: Towards Language Model Architectures Interpretable by Design
Deep neural networks divide and conquer dihedral multiplication
Flowers: A Warp Drive for Neural PDE Solvers
Non-Monotonic Autoregressive Sequence Model
Position: We Need AI Efficiency Incentives for Accessibility and Sustainability
Scaling, Benchmarking, and Reasoning of Vision-Language Agents for Mobile GUI Navigation
CoGeoAD: Hierarchical Color-Geometric Fusion with Multi-View Attention for Zero-Shot 3D Anomaly Detection
Zero-shot Active Mapping via Fused 360-BEV Representations and Vision–Language Models
VlogReward: Learning Multi-Dimensional Evaluation for Vlog Editing
Hyperbolic Hierarchical Alignment for Video-Based Visible-Infrared Person Re-Identification
Position: AI Capabilities Are Not Increasing Exponentially
Video-BCI: Bayesian Cognitive Integration of Self-Prior Hypotheses for Video Understanding
Stabilizing Native Low-Rank LLM Pretraining
MM-Snowball: Evaluating and Mitigating Hallucination Snowballing in Multimodal Multi-Turn Dialogue
HiCI: Hierarchical Construction–Integration for Long-Context Attention
Q-CLIP: Unleashing the Power of Vision-Language Models for Video Quality Assessment through Unified Cross-Modal Adaptation
Seeing Realism from Simulation: Efficient Video Transfer for Vision-Language-Action Data Augmentation
Motion Dynamics Learning for Few-Shot Embodied Adaptation
Continual GUI Agents
Fair-FedMOE: Group-Fair One-Shot Federated Learning via Prototype-Guided Experts for Medical Imaging Analysis
Rethinking Genomic Modeling Through Optical Character Recognition
Zero-Shot Rankability: Revealing Latent Ordinal Structure in Multimodal Large Language Models via Language
DTKG: Dual-Track Knowledge Graph-Verified Reasoning Framework for Multi-Hop QA
A Direct Approach for Handling Contextual Bandits with Latent State Dynamics
Benchmarking Physics-Informed Time-Series Models for Operational Global Station Weather Forecasting
GenShield: Unified Detection and Artifact Correction for AI-Generated Images
OPTION: Optimal Transport–Guided Flow Matching for Incomplete and Unaligned Multi-View Clustering
MobileFusion: Mobile-Friendly Infrared and Visible Image Fusion via Structural Re-parameterization
Position: Metaphysical Concepts in AI Should Be Judged by Their Consequences
VAnim: Rendering-Aware Sparse State Modeling for Structure-Preserving Vector Animation
SPAR: Support-Preserving Action Rectification
SMAC: Score-Matched Actor-Critics for Robust Offline-to-Online Transfer
HiMAP-Travel: Hierarchical Multi-Agent Planning for Long-Horizon Constrained Travel
Q-SAM: Unlocking Sharpness-Aware Minimization for Generalization in Offline Reinforcement Learning
Towards Efficient and Expressive Offline RL via Flow-Anchored Noise-conditioned Q-Learning
SVL: Goal-Conditioned Reinforcement Learning as Survival Learning
Learning to Watch: Active Video Anomaly Understanding via Interleaved Policy Optimization
BFTS: Thompson Sampling with Bayesian Additive Regression Trees
Discriminative Visual Process Rewards for Scaling Thinking at Test-Time with Images
Improving Diffusion Planners by Self-Supervised Action Gating with Energies
Geometric Control of Out-of-Distribution Shift in Safe Offline RL
Boosting CVaR Policy Optimization with Quantile Gradients
From Imagined Futures to Executable Actions: Mixture of Latent Actions for Robot Manipulation
Position: Good Embodied Reward Models Need Bad Behavior Data
Stabilizing the Q-Gradient Field for Policy Smoothness in Actor-Critic Methods
CINOC: Cardinality-Invariant Neural Operator Policies for Scalable PDE Control
Position: Generative Distributional Integrity against Backdoor Attacks
From Interaction Trajectories to Prompt Rules: Credit Assignment for Multi-Agent Prompt Optimization
Posterior Behavioral Cloning: Pretraining BC Policies for Efficient RL Finetuning
Scalable Reinforcement Learning via Adaptive Batch Scaling
Softmax as Linear Attention in the Large-Prompt Regime: a Measure-based Perspective
Fast Non-Episodic Finite-Horizon RL with K-Step Lookahead Thresholding
Improved Bounds for Private and Robust Alignment
Recursive Monte-Carlo Tree Search
HodgeFlow Policy Search by Topologically Dissecting Temporal-Difference Signals in Non-Markovian Environments
Time-Consistent Robust Multi-Objective Reinforcement Learning via a Bellman–Isaacs Weight-Adversary Recursion
Learning-Augmented Online Covering Problems
Fair Decisions from Calibrated Scores: Achieving Optimal Classification While Satisfying Sufficiency
Subgroup Discovery with the Cox Model
AREA: Attribute Extraction and Aggregation for CLIP-Based Class-Incremental Learning
Theoretical Analysis of Sparse Optimization with Reparameterization, Weight Decay, and Adaptive Learning Rate
BAS: Bridging Adam and SignSGD for Memory-Efficient LLM Training
Flex-Forcing: Towards a Unified Autoregressive and Bidirectional Video Diffusion Model
WeightCLIP: Aligning Datasets and Models for Weight Space Learning
SkelHCC: A Hyperbolic CLIP-Driven Cache Adaptation Framework for Skeleton-based One-Shot Action Recognition
FlatLand: Personalized Graph Federated Learning via Tailored Lorentz Space
Censoring with Plausible Deniability: Asymmetric Local Privacy for Multi-Category CDF Estimation
ActiveScope: Actively Seeking and Correcting Perception for MLLMs
Implicit Turn-Wise Policy Optimization for Proactive User-LLM Interaction
From Teacher Pathways to Invariant Manifolds: Consensus Subspace Distillation for TSFMs
LOZO+: Provably Efficient Zeroth-Order Fine-Tuning via Greedy Low-Rank Subspace Selection
WFR-MFM: One-Step Inference for Dynamic Unbalanced Optimal Transport
Universal Representation of Generalized Convex Functions and their Gradients
iWorld-Bench: A Benchmark for Interactive World Models with a Unified Action Generation Framework
Accelerating Regression Tasks with Quantum Algorithms
Annotations Mitigate Post-Training Mode Collapse
Rethinking Personalization in Large Language Models at the Token Level
InfoLaw: Information Scaling Laws for Large Language Models with Quality-Weighted Mixture Data and Repetition
Evaluating and Steering Modality Preferences in Multi-modal LLMs
BiCrossNet with Decoupled Dual Generators: A Parameter‑Efficient and Generalizable Few‑Shot Custom Gesture Recognition Framework
Uncovering Grounding IDs: How External Cues Shape Multi-Modal Binding
Asymptotic Theory of Iterated Empirical Risk Minimization, with Applications to Active Learning
Breaking the Scale Barrier: One-Shot Knowledge Transfer via Frequency Transform
When to Memorize and When to Stop: Gated Recurrent Memory for Long-Context Reasoning
STABLE: Simulation-Ready Tabletop Layout Generation via a Semantics–Physics Dual System
Stream RAG: Instant and Accurate Spoken Dialogue Systems with Streaming Tool Usage
Polaris: Coupled Orbital Polar Embeddings for Hierarchical Concept Learning
Generative Neural Operators through Diffusion Last Layer
Safety Recovery in Reasoning Models Is Only a Few Early Steering Steps Away
Learning to Self-Verify Makes Language Models Better Reasoners
Safety-Efficacy Trade Off: Robustness against Data-Poisoning
Unsupervised Process-Aware Coreset Selection for In-Context Learning
MME-Reasoning: A Broad-Spectrum Benchmark for Evaluating Logical Reasoning in MLLMs
CriticalKV: Optimizing KV Cache Eviction from an Output Perturbation Perspective
Towards Understanding Steering Strength
Patterning: The Dual of Interpretability
Tvcache: A Tool-Value Cache for Post-Training LLM Agents
Unifying Low Dimensional Spectra in Deep Learning
Optimal Stopping in Latent Diffusion Models
Information dynamics and Memory in Neural Networks through Fisher Information Diffusion
Riemannian Dueling Optimization
Geometric Pocket-Centric Protein Encoding for Polypharmacology-Guided Multi-Target Drug Design
Learning to Share: Selective Memory for Efficient Parallel Agentic Systems
Floating-Point Networks with Automatic Differentiation Can Represent Almost All Floating-Point Functions and Their Gradients
A Benchmark and Framework for Evaluating Next Action Predictions in Spreadsheets
Multi-Level Strategic Classification: Incentivizing Improvement through Promotion and Relegation Dynamics
Delegation and Verification under AI
Probably Approximately Correct Labels
Knowing Who, Not How Much: Learning-Augmented Mechanisms for Consumer Utility Maximization
Prescriptive Scaling Reveals the Evolution of Language Model Capabilities
Tree-Structured Orthonormal Decomposition of the Aitchison Simplex
FedGain: Toward Negative-Gain-Free Client Collaboration in Federated Learning
Beyond Explicit Edges: Robust Reasoning over Noisy and Sparse Knowledge Graphs
Beyond Benchmarks: Toward Causally Faithful Evaluation of Large Language Models
Routing and Reasoned Evaluation with Large Language Models
CodeTaste: Can LLMs Generate Human-Level Code Refactorings?
SoftJAX & SoftTorch: Empowering Automatic Differentiation Libraries with Informative Gradients
Convolutional Learnable-Group Weightless Neural Network
Rethinking Time-Series Imputation as Conditional Inference along Temporal Evolution
Relevance-Based Embeddings: Lightweight Candidate Retrieval via Heavy-Ranker Calls
Independent Component Discovery in Temporal Count Data
Modeling Attributional Style at Scale: A Dataset and Analysis for Psychological Attribution Assessment and Reframing
Towards Rule-Based Knowledge Sharing in Federated Learning
Wait, Wait, Wait... Why Do Reasoning Models Loop?
Contrastive Order Learning: A General Framework for Ordinal Regression
Learning Generalized Label Distributions
Hard Labels In! Rethinking the Role of Hard Labels in Mitigating Local Semantic Drift
DC-W2S: Dual-Consensus Weak-to-Strong Training for Reliable Process Reward Modeling in Biological Reasoning
Divisiveness-Consistent Label Distribution Learning
Distilling Linearized Behavior into Non-linear Fine-Tuning for Effective Task Arithmetic
Words Towards Explainability: Caption Label-Free Learning via Dual Loop Agentic Time Series Captioning
Gradient Transformer: Learning to Generate Updates for LLMs
Beyond Buffer Limits: Energy-Based Data Reassembly for Continual Learning
PLATE: Plasticity-Tunable Efficient Adapters for Geometry-Aware Continual Learning
Spectral Imbalance Causes Forgetting in Low-Rank Continual Adaptation
Particle Flow for Learning from Label Proportions
CSD: Content-aware Speculative Decoding for Efficient Image Generation
Towards Efficient Large Language Reasoning Models via Extreme-Ratio Chain-of-Thought Compression
Efficient Equivariant High-Order Crystal Tensor Prediction via Cartesian Local-Environment Many-Body Coupling
GR-LoRA: Gradient-Recycling Low-Rank Adaptation for Class-Incremental Learning
Personalized Additive Modeling for Multi-level Federated Learning
SIPO: Stabilized and Improved Preference Optimization for Aligning Diffusion Models
Explicitly Modeling Censoring Produces Superior Survival Predictors
Natural Hypergradient Descent: Algorithm Design, Convergence Analysis, and Parallel Implementation
Unifying Adversarial Robustness and Training Across Text Scoring Models
Towards Long-Horizon Interpretability: Efficient and Faithful Multi-Token Attribution for Reasoning LLMs
Exactly Computing do-Shapley Values
The Catastrophic Failure of *the* k-Means Algorithm in High Dimensions, and How Hartigan's Algorithm Avoids It
Functional Decomposition and Shapley Interactions for Interpreting Survival Models
Breaking the Reversal Curse in Autoregressive Language Models via Identity Bridge
Uncovering Competency Gaps in Large Language Models and Their Benchmarks
PMSPO: Progressive Matching and Semantic-Aware Policy Optimization for Camouflaged Object Detection
Alignment Pretraining: AI Discourse Causes Self-Fulfilling (Mis)alignment
MORALISE: A Structured Benchmark for Moral Alignment in Visual Language Models
Hyper-LLaVA: Hyperbolic Uncertainty-aware Modality-Balanced Routing for Multimodal Continual Instruction Tuning
The Oversight Game: Learning to Cooperatively Balance an AI Agent's Safety and Autonomy
Learning When to Act or Refuse: Guarding Agentic Reasoning Models for Safe Multi-Step Tool Use
Z-Erase: Enabling Concept Erasure in Single Stream Diffusion Transformers
Knothe-Rosenblatt Quantile Regression for Risk-sensitive Multi-objective Reinforcement Learning
Emergence of Hierarchical Emotion Organization in Large Language Models
A Game-Theoretic Analysis of Attacks on Large Language Models via Compositional Skills
DualOptim+: Bridging Shared and Decoupled Optimizer States for Better Machine Unlearning in Large Language Models
DGS-Net: Distillation-Guided Gradient Surgery for CLIP Fine-Tuning in AI-Generated Image Detection
Gaming Consensus: Coordinated Manipulation in Crowdsourced Fact-Checking
Autoregressive, Yet Revisable: In Decoding Revision for Secure Code Generation
WatchLog: Efficient and Interpretable Event Reasoning for Endpoint Detection and Response Logs with Multimodal LLMs
Real Data Lies: Unveiling and Closing the Quality Shortcut in Generalizable AI-Generated Video Detection
Dissecting the Safety Circuit: Neuronal Intervention for Transferable Adversarial Attacks on VLMs
Next-Gen CAPTCHAs: Leveraging the Cognitive Gap for Scalable and Diverse GUI-Agent Defense
PhoStream: Benchmarking Real-World Streaming for Omnimodal Assistants in Mobile Scenarios
Co-RedTeam: Orchestrated Security Discovery and Exploitation with LLM Agents
Ripple Perturbations Through Structure: Likelihood-Constrained Adversarial Attacks on Heterogeneous Tabular Data
Continuous-Time Piecewise-Linear Recurrent Neural Networks
Expressive Graph Neural Networks via Equivariant Use of Noise
Evolving Interpretable Constitutions for Multi-Agent Coordination
RTInfer: Real-Time Inference of Multiple DNNs on Edge GPUs
QPKO: Differentiable QP-Embedded Deep Koopman Framework for Modeling Nonlinear Systems
Meta-Black-Box Optimization Can Do Search Guidance for Expensive Constrained Multi-Objective Optimization
Equilibrium Reasoners: Learning Attractors Enables Scalable Reasoning
Stabilizing Equation Learning via Zero-Point Constraints
Learning When to Attend: Conditional Memory Access for Long-Context LLMs
Towards Diverse Scientific Hypothesis Search with Large Language Models
Align Forward, Adapt Backward: Closing the Discretization Gap in Logic Gate Networks
Feature-Aware (Hyper)graph Generation via Next-Scale Prediction
Quantum latent distributions in deep generative models
STAR-VAE: Structured Topology-Aware Regularization for Audio Reconstruction and Generation
DetailMaster: Can Your Text-to-Image Model Handle Long Prompts?
Overclocking Electrostatic Generative Models
Sparse Autoencoders are Topic Models
Which Algorithms Can Graph Neural Networks Learn?
Is Graph Mixup Beneficial? Investigating Interpolation And Empirical Performance of Graph Mixup Methods
Transformers Learn the Optimal DDPM Denoiser for Multi-Token GMMs
On Efficient Scaling of GNNs via IO-Aware Layers Implementations
Identifiable Equivariant Networks are Layerwise Equivariant
Gradient-Aware Scheduling: Coupling Curriculum and Staleness for Async Reinforcement Learning
Attention Sinks as Internal Signals for Hallucination Detection in Large Language Models
Omni-Perception Policy Optimization for Multimodal Emotion Reasoning
CUPID in the Model Zoo: Online Matchmaking for Selecting Your Dream LLM
A Critical Look at Targeted Instruction Selection: Disentangling What Matters (and What Doesn’t)
Aligning Tree-Search Policies with Fixed Token Budgets in Test-Time Scaling of LLMs
LLMInertia: Adaptive Counter-Inertial Reasoning to Improve Evidence Faithfulness in Large Language Models
Gecko: A Simulation Environment with Stateful Feedback for Refining Agent Tool Calls
PlugMem: A Task-Agnostic Plugin Memory Module for LLM Agents
Optimal Splitting of Language Models from Mixtures to Specialized Domains
When RAG Hurts: Diagnosing and Mitigating Attention Distraction in Retrieval-Augmented LVLMs
SAGE: A Dataflow-Native Framework for Modular, Controllable, and Transparent LLM-Augmented Reasoning
Bayesian model selection and misspecification testing in imaging inverse problems only from noisy and partial measurements
From Prompts to Responses: Dual-Sided Data Leakage and Defense in Split Large Language Models
One-Way Policy Optimization for Self-Evolving LLMs
Rethinking LLM Ensembling from the Perspective of Mixture Models
LittleBit-2: Maximizing the Spectral Energy Gain in Sub-1-Bit LLMs via Latent Geometry Alignment
$\mu$pscaling small models: Principled warm starts and hyperparameter transfer
Prioritize the Process, Not Just the Outcome: Rewarding Latent Thought Trajectories Improves Reasoning in Looped Language Models
SMART: Scalable Mesh‑free Aerodynamic Simulations from Raw Geometries using a Transformer‑based Surrogate Model
Post-Training LLMs as Better Decision-Making Agents: A Regret-Minimization Approach
Truthfulness Does Not Scale Like Reasoning: Why Polling Fails as a Proxy Verifier
Efficient Skill Grounding via Code Refactoring with Small Language Models
MoDA: Modulation Adapter for Fine-Grained Visual Understanding in Instructional MLLMs
FAFO: Lossy KV Cache Compression for Lossless Inference Acceleration via Draftless Fumble Decoding
Imagination Helps Visual Reasoning, But Not Yet in Latent Space
Sycophancy Towards Researchers Drives Performative Misalignment
Conformal Path Reasoning: Trustworthy Knowledge Graph Question Answering via Path-Level Calibration
CausalProfiler: Generating Synthetic Benchmarks for Rigorous and Transparent Evaluation of Causal Machine Learning
TAMPO: Task- and Model-Aware Automatic Prompt Optimization for Auto-Routing in LLM-based Systems
COBRA: Contribution-Based Bayesian Rank Allocation for Parameter-Efficient Fine-Tuning
What Makes Effective Supervision in Latent Chain-of-Thought: An Information-Theoretic Analysis
Task-and-Model-Aware Fractal-Consistency for Efficient LLM Reasoning
Token-Level LLM Collaboration via FusionRoute
Convergent World Representations and Divergent Tasks
TextAtlas5M: A Large-Scale Dataset for Long Text Image Generation
Understanding Reasoning Collapse in LLM Agent Reinforcement Learning
Balancing Learning Rates Across Layers: Exact Two-Step Dynamics and Optimal Scaling in Linear Neural Networks
Steering Out-of-Distribution Generalization with Concept Ablation Fine-Tuning
BTSP-CAM: A Brain-Inspired Geometric Memory for Class-Incremental Learning
TPV: Parameter Perturbations Through the Lens of Test Prediction Variance
Focus and Dilution: The Multi-stage Learning Process of Attention
The Geometric Mechanics of Contrastive Representation Learning: Alignment Potentials, Entropic Dispersion, and Cross-Modal Divergence
GXPO: Group Cross-Lingual Relative Policy Optimization for Code Generation
Revisiting the Volume Hypothesis
TopoDistill: Distilling Global System Topology for Causal Discovery in Multivariate Time Series
The Stability of Singular Distribution: A Spectral Perspective on the Two-Phase Dynamics of Language Model Pre-training
Turning Drift into Constraint: Robust Reasoning Alignment in Non-Stationary Multi-Stream Environments
On the origin of neural scaling laws: from random graphs to natural language
Scalable Kronecker-Factored Fisher Approximation for Neural Network Parameter Sensitivity
Dissecting Quantization Error: A Concentration-Alignment Perspective
Reliable Thinking with Images
Cognitive Fatigue in Autoregressive Transformers: Formalization and Measurement
LATMiX: Learnable Affine Transformations for Microscaling Quantization of LLMs
On the Expressive Power of Permutation-Equivariant Weight-Space Networks
SpatialJB: How Text Distribution Art Becomes The "Jailbreak Key" for LLM Guardrails
A Minimax Approach for Optimal Intervention Policy Learning with Two-Stage Outcomes
Shortcut-Resistant CAM Distillation for Long-Tailed Recognition
Forgetting Whenever You Want: A Decentralized Continual Learning Framework with On-Demand Unlearning
Tracing the Dynamics of Refusal: Exploiting Latent Refusal Trajectories for Robust Jailbreak Detection
Probing the Inductive Bias of Neural Networks through Learning Random Cellular Automata
T2AV-Compass: Towards Unified Evaluation for Text-to-Audio-Video Generation
Lie-Algebraic Acceleration of Neural Koopman Dynamics
Euler–Poincaré Neural Dynamics: A Geometric-Mechanics Framework for Scientific Simulation
Solving Inverse Problems with Flow-based Models via Model Predictive Control
VividCam: Learning Unconventional Camera Motions from Virtual Synthetic Videos
GemDepth: Geometry-Embedded Features for 3D-Consistent Video Depth
One-Step Graph-Structured Neural Flows for Irregular Multivariate Time Series Classification
Mixture of Distributions Matters: Dynamic Sparse Attention for Efficient Video Diffusion Transformers
$\texttt{Multi}^2$: Hierarchical Multi-Agent Decision-Making with LLM-Based Agents in Interactive Environments
RefChess: Training-Free Contextual Search for Zero-Shot Referring Image Segmentation
PixCLIP: Towards Fine-grained Vision-Language Understanding via Any-granularity Pixel-Text Alignment
G$^2$TAM: Geometry Grounded Track Anything Model
AmbiRefer3D: 3D Visual Grounding with Referential Ambiguity
SLAE: Strictly Local All-atom Environment for Protein Representation
Towards Docking-oriented De Novo Ligand Design via Gradient Inversion
MolAlign3D: Enhancing Fixed-Dimensional E(3)-Equivariant Latent Space for High-Fidelity 3D Molecular Reconstruction and Editing
VecMol: Vector-Field Representations for 3D Molecule Generation
InfoGlobe: Local-and-Global Information-Preserving Statistical Manifold Learning for Single-Cell Transcriptomics
Object-level Semantic and Spatial Distillation for Open Vocabulary Detection
MoLF: Mixture-of-Latent-Flow for Pan-Cancer Spatial Gene Expression Prediction from Histology
Position: Quantum Deep Learning Still Needs a Quantum Leap
Criterion-Conditional In-Context Learning: Evaluating Criterion-Shift Adaptation in Vision-Language Models
CellBRIDGE: Learning Cellular Trajectories via Interaction-Aware Alignment
MedSIGHT: Towards Grounded Visual Comprehension in Medical Large Vision-Language Models
ProtDBench: A Unified Benchmark of Protein Binder Design and Evaluation
Med-Scout: Curing MLLMs' Geometric Blindness in Medical Perception via Geometry-Aware RL Post-Training
COFT: Counterfactual–Conformal Decoding for Fair Chain‑of‑Thought Reasoning in Large Language Models
How Far Can LLM Agents Reason with Tables? Benchmarking Multi-Turn Agentic Table Question Answering in the Wild
Neural-Inspired Modeling of Auditory Selection and Compensation for Audio-Visual Speech Separation
SAM Audio: Segment Anything in Audio
Toward Robust Multilingual Adaptation of LLMs for Low-Resource Languages
Quant VideoGen: Auto-Regressive Long Video Generation via 2-Bit KV-Cache Quantization
PosterAgent: Agentic Poster Generation via Stage-Aware Reinforcement Learning
Scaling Laws and Architectural Frontiers in Metagenomic Foundation Models
ConsMSA: Semantic Distribution Consistency Learning for Multimodal Sentiment Analysis
NaviAgent: Graph‑Driven Bilevel Planning for Scalable Tool Orchestration
Do Audio LLMs Listen or Read? Analyzing and Mitigating Paralinguistic Failures with VoxParadox
OMP: One-step Meanflow Policy with Directional Alignment
CollabBench: Benchmarking and Unleashing Collaborative Ability of LLMs with Diverse Players via Proactive Engagement
AgentSelect: Benchmark for Narrative Query-to-Agent Recommendation
When Data Is Scarce: Scaling Sparse Language Models with Repeated Training
MEnvAgent: Scalable Polyglot Environment Construction for Verifiable Software Engineering
HECTOR: Hybrid Editable Compositional Object References for Video Generation
SD-MoE: Spectral Decomposition for Effective Expert Specialization
CALM Before the STORM: Unlocking Native Reasoning for Optimization Modeling
PRPO: Paragraph-level Policy Optimization for Vision-Language Deepfake Detection
ReNF: Rethinking the Design of Neural Long-Term Time Series Forecasters
The Hippocampal Place Field Gradient: A Bio-inspired Framework Building Multiscale Representation for Better Sample Efficiency
Reward Learning through Ranking Mean Squared Error
Provably Efficient Policy-Reward Co-Pretraining for Adversarial Imitation Learning
Correct Looks Better: Pairwise Comparisons Reveal Accuracy Rankings
Noise-Guided Transport: Imitation Learning from Random Priors
MemOCR: Layout-Aware Visual Memory for Efficient Long-Horizon Reasoning
Population-Aware Imitation Learning in Mean-field Games with Common Noise
COLLIE: Guiding Skill Discovery in Semantically Coherent Latent Space
MPFM: Cross Multi-Domain Prototype Flow Matching for Log Anomaly Detection
Geometric Coherence Learning for Structuring Value Functions in Plain MDPs
RuCL: Stratified Rubric-Based Curriculum Learning for Multimodal Large Language Model Reasoning
POLIA: Policy Optimization with Visual-Object-Level Intrinsic Advantage for Multimodal Reasoning
RL-SPH: Learning to Achieve Feasible Solutions for Integer Linear Programs
DAVE: Distribution-aware Attribution via ViT Gradient Decomposition
Text Before Vision: Staged Knowledge Injection Matters for Agentic RLVR in Ultra-High-Resolution Remote Sensing Understanding
ProbeLLM: Automating Principled Diagnosis of LLM Failures
Extracting alignment data in open models
Mitigating Reward Hacking in LLM-based Recommendation: A Preference Optimization Approach
Robust Human-AI Complementarity under Uncertainty
FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs
Calibrated Multimodal Representation Learning with Missing Modalities
Column Thresholding for Sparse Spiked Wigner Models: Improved Signal Strength Requirements
Scalable Single-Cell Gene Expression Generation with Latent Diffusion Models
Architecture Matters for Multi-Agent Security
LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation
Generative Modeling of Discrete Latent Structures via Dynamic Policy Gradients
Experience Augmented Policy Optimization for LLM Reasoning
FPTQuant: Function-Preserving Transforms for LLM Quantization
Text Has Curvature
SemRep : Generative Code Representation Learning with Code Transformations
Localize and Neutralize: Gradient-Guided Token Suppression Against Visual Prompt Injection Attack
Revisiting Anisotropy in Language Transformers: The Geometry of Learning Dynamics
VisualPuzzles: Decoupling Multimodal Reasoning Evaluation from Domain Knowledge
Geometric Convergence of Gauss–Newton for Neural Networks: Riemannian Geometry and Adaptive Damping
MMD Guidance: Training-Free Distribution Adaptation for Diffusion Models via Maximum Mean Discrepancy Guidance
Conservation Laws for Modern Neural Architectures
How much can language models memorize?
A Formal Comparison Between Chain of Thought and Latent Thought
Tilt Matching for Scalable Sampling and Fine-Tuning
MUSE: Resolving Manifold Misalignment in Visual Tokenization via Topological Orthogonality
MASPO: Joint Prompt Optimization for LLM-based Multi-Agent Systems
Prism: Spectral-Aware Block-Sparse Attention
Breaking the Self-Confirming Loop: Diagnosing and Mitigating Systemic Reward Bias in Self-Rewarding RL
Lavida-R1: Advancing Reasoning for Unified Multimodal Diffusion Language Models
LangForce: Bayesian Decomposition of Vision Language Action Models via Latent Action Queries
Simultaneous Confidence Bounds for Aggregated Effects via Exact Subset Optimization
Sparser Block-Sparse Attention via Token Permutation
DC-Leap: Training-Free Acceleration of dLLMs via Draft-Guided Contiguous Leaping Decoding
A Recursive Decomposition Framework for Causal Structure Learning in the Presence of Latent Variables
Addressing Semantic Blind Spots in Text-to-SQL via Component Pre-generation and AST Matching Rewards
MER-DG: Modality-Entropy Regularization for Multimodal Domain Generalization
Motion Planning in Compressed Representation Spaces
Rank-Aware Spectral Bounds on Attention Logits for Stable Low-Precision Training
Post-Hoc Merging is Not Enough: Many-Shot Model Merging with Loss-Gap Balancing
Transfer Learning in Nonparametric Regression with Deep ReLU Networks
Latent-Guided Cooperative Energy-Based Models
Delayed Momentum Aggregation: Communication-efficient Byzantine-robust Federated Learning with Partial Participation
EigenCache: Rethinking Diffusion Acceleration as Covariance-Optimal Forecasting and Submodular Information Allocation
Efficient Training-Free Multi-Token Prediction via Embedding-Space Probing
PDAgent: An LLM-Driven Autonomous Agent Framework Towards *In Silico* Protein Design via Directed Mutation
Reducing Per-Sample Harm in Stochastic Optimization
Entropy-aware Span-Constrained Optimal Transport for Robust Cross-Tokenizer Knowledge Distillation
Unlocking Cross-Modal Biosignal Synthesis: A Temporally-Aware VAE-Diffusion Model
Mem-T: Densifying Rewards for Long-Horizon Memory Agents
SFCLTA: Spectral Fusion Contrastive Learning with Topology-Adaptive Graph Augmentation
Causal discovery for time series with endogenous context variables
Identifying Latent Concepts and Structures for Generalized Category Discovery
AlgoVeri: An Aligned Benchmark for Verified Code Generation on Classical Algorithms
Reliable Neighborhood-Aware Multi-View Outlier Detection
ANCHOR: Abductive Network Construction with Hierarchical Orchestration for Reliable Probability Inference in Large Language Models
3ViewSense: Spatial and Mental Perspective Reasoning from Orthographic Views in Vision-Language Models
Unsupervised Hierarchical Skill Discovery
Where Rectified Flows Leak: Characterising Membership Signals Along the Interpolation Path
Optimal Rates for Feasible Payoff Set Estimation in Games
“very likely” Means “uncertain”? How LLMs Diverge from Humans in Linguistic Uncertainty Quantification
*MemPot*: Defend Against Memory Extraction Attack with Optimized Honeypots
(Be Cautious!) Bio-Foundation Models Are Not Yet Robust to Biologically Plausible Perturbations and ML Transformations
Localizing Memorized Regions in Diffusion Models via Coordinate-Wise Curvature Differences
AdaMeZO: Adam-style Zeroth-Order Optimizer for LLM Fine-tuning Without Maintaining the Moments
Think in Cloud, Look at Edges: Semantic-Driven Query Decomposition for Efficient Video Reasoning
Gradient-Free Approaches is a Key to an Efficient Interaction with Markovian Stochasticity
Klein Hyperbolic Metric Learning
RelayCaching: Accelerating LLM Collaboration via Decoding KV Cache Reuse
Imposing Boundary Conditions on Neural Operators via Learned Function Extensions
The Entropic Signature of Class Speciation in Diffusion Models
Few-Shot Design Optimization by Exploiting Auxiliary Information
Uni-DocRobust: Universal Plug-and-Play Robustness Enhancement for Multi-modal LLMs via Feature Restoration
Balancing Plasticity and Stability with Fast and Slow Successor Features
Calibrating Uncertainty for Zero-Shot Adversarial CLIP
Restoring Exploration after Post-Training: Latent Exploration Decoding for Large Reasoning Models
Parsimonious Learning-Augmented Online Metric Matching
Language Model Circuits Are Sparse in the Neuron Basis
LeakGFN: Robust Molecular Generation in Generative Flow Networks via Flow Decomposition
PPI Candidate Ranking: Large-Scale Evaluation of a Domain Knowledge–Guided Pipeline
From Growing to Looping: A Unified View of Iterative Computation in LLMs
A model of errors in transformers
More Edits, More Stable: Understanding the Lifelong Normalization in Sequential Model Editing
Bi-Anchor Interpolation Solver for Accelerating Generative Modeling
Discovering Differences in Strategic Behavior between Humans and LLMs
Origo: Interpretable Multi-physics PDE Foundation Model through Neural Operator Splitting
LagLLM: LLM-empowered lead–lag dependency learning for spatial-temporal time series forecasting
OrchJail: Jailbreaking Tool-Calling Text-to-Image Agents by Orchestration-Guided Fuzzing
Self-Supervised Learning as Discrete Communication
HVR-Met: A Hypothesis-Verification-Replanning Agentic System for Extreme Weather Diagnosis
Geometric Rate–Distortion Invariance for Domain Generalization
Low-dimensional topology of deep neural networks
Second-Order Smooth Planning with Optimal-Transport Bellman Smoothing
What Information Matters? Graph Out-of-Distribution Detection via Tri-Component Information Decomposition
4DPC$^2$hat: Towards Dynamic Point Cloud Understanding with Failure-Aware Bootstrapping
Variance Driven Exploration: A Provable and Efficient Methodology for Pure Exploration in Highly Stochastic Environments
Batch Normalization for Neural Networks on Complex Domains
RepetitionCurse: Measuring and Understanding Router Imbalance in Mixture-of-Experts LLMs under DoS Stress
INDUCTION: Finite-Structure Concept Synthesis in First-Order Logic
Sharpness-Aware Pretraining Mitigates Catastrophic Forgetting
A proximal ADMM for multiblock problems with block anti-upper triangular constraints
Building Social World Model with Large Language Models
Efficient and Minimax Optimal In-context Nonparametric Regression with Transformers
Pressure Reveals Character: Behavioural Alignment Evaluation at Depth
Linguistic Relative Policy Optimization for Video Anomaly Reasoning
ScoreMatchingRiesz: Score Matching for Debiased Machine Learning and Policy Path Estimation
Learning to Evict from Key-Value Cache
DSB: Dynamic Sliding Block Scheduling for Diffusion LLMs
Sketch-Based Low-Rank Model Merging with Shared Circulant Transforms
QUATRO: Query-Adaptive Trust Region Policy Optimization for LLM Fine-tuning
Learning What to Generate: A Reinforcement Learning-based Closed-Loop Augmentation Framework for Person Re-identification
MIRA: A Score for Conditional Distribution Accuracy and Model Comparison
$\texttt{PRISM}$:A 3D Probabilistic Neural Representation for Interpretable Shape Modeling
Learning Manifold Data with Flow Matching
Trajectory Consistency for One-Step Generation on Euler Mean Flows
High-Dimensional Sensitivity Analysis for Genomic Studies: An Adversarial Framework for Learning Worst-Case Latent Confounders
Alleviating Observation Bias via Causal-Invariant Meta-Learning for Unbalanced Incomplete Multi-view Clustering
Learning to Approximate Uniform Facility Location via Graph Neural Networks
SIKA-GP: Accelerating Gaussian Process Inference with Sparse Inducing Kernel Approximations for Bayesian Deep Learning
Learning Query-Aware Budget-Tier Routing for Runtime Agent Memory
On Structured State-Space Duality
No More K-means: Single-Stage Sparse Coding for Efficient Multi-Vector Retrieval
Trust It or Not: Evidential Uncertainty for Feed-Forward 3D Reconstruction with Trust3R
Language Generation with Feedback: Queries and Mistakes
Constructing Industrial-Scale Optimization Modeling Benchmark
Dynamic Compression Flows for Neuroscience Data
Bioacoustic Geolocation: Species Sounds as Geographic Signals
Spectral Guidance for Flexible and Efficient Control of Diffusion Models
Trajectory-Level Data Augmentation for Offline Reinforcement Learning
Information-Theoretic Generalization Bounds for VAEs: A Role of Encoder and Latent Variable
Learning Dynamic Stability Landscapes in Synchronization Networks
An Empirical Study on the Resilience of Partial Merging to Model Clone Attacks
Generalization of Gibbs and Langevin Monte Carlo Algorithms in the Interpolation Regime
Biases in the Blind Spot: Detecting What LLMs Fail to Mention
IRPM: Intergroup Relative Preference Modeling for Pointwise Generative Reward Models
Faster Than Flash: Exploiting Attention Sparsity for Efficient Long-Context Decoding
Chain-of-Thought Reasoning In The Wild Is Not Always Faithful
Base Models Know How to Reason, Thinking Models Learn When
Upper-Linearizability of Online Non-Monotone DR-Submodular Maximization over Down-Closed Convex Sets
Geodesic Calculus on Implicitly Defined Latent Manifolds
Adaptive Volumetric Mechanical Property Fields Invariant to Resolution
CrossQ: Task-Aligned Cross-Token Conditional Quantization for Late Interaction Retrieval
Diffusion Models Are Statistically Optimal for Learning Low-Dimensional Multi-Modal Distributions
Unison: Benchmarking Unified Multimodal Models via Synergistic Understanding and Generation
Scaling Inference-Time Computation via Opponent Simulation: Enabling Online Strategic Adaptation in Repeated Negotiation
Detecting and Filtering Unsafe Training Data via Data Attribution with Denoised Representation
Where Detectors Fail: Probing Generative Space for Generalizable AI-Generated Image Detection
When Preference Labels Fall Short: Aligning Diffusion Models from Real Data
Text-Conditional JEPA for Learning Semantically Rich Visual Representations
Online Social Welfare Function-based Resource Allocation
HiST: A Hierarchical Sparse Transformer for Cross-Modal Spatial Transcriptomics Modeling
SDiD：Shared diffusion prior for efficient distributed stereo image compression
Learning-Guided Integration Contours Construction for Fast Large-Scale Generalized Eigensolvers
DIVER: Diving Deeper into Distilled Data via Expressive Semantic Recovery
DFlash: Block Diffusion for Flash Speculative Decoding
Computationally-efficient Graph Modeling with Refined Graph Random Features
Neuro-Fuzzy Concept Learning for Interpretable Large Multimodal Models
Causal-JEPA: Learning World Models through Object-Level Latent Masking
Rethinking Contrastive Learning for Graph Collaborative Filtering: Limitations and a Simple Remedy
scDEBART: Predicting in silico Single-Cell Perturbation Responses via Large-Scale Differential Expression Learning
Proximal-IMH: Proximal Posterior Proposals for Independent Metropolis–Hastings with Approximate Operators
PAMD: Structured Adaptive Distances for Bisimulation Representations in Visual Reinforcement Learning
Self-evolving LLM agents with in-distribution Optimization
MET-Bench: Multimodal Entity Tracking for Evaluating the Limitations of Vision-Language and Reasoning Models
Strategic Candidacy in Generative AI Arenas
Training Data Efficiency in Multimodal Process Reward Models
CRAMER: Control via Request-Aware Masking for Editing Recommenders
Leaderboard Incentives: Model Rankings under Strategic Post-Training
FormulaCode: Evaluating Agentic Optimization on Large Codebases
ARC-Decode: Accelerated Decoding with Risk-Bounded Acceptance
Prism-MoE: Efficient Dense-to-MoE Conversion for Visual Autoregressive Generation
Behavior-Invariant Task Representation Learning with Transformer-based World Models for Offline Meta-Reinforcement Learning
MARS: Modular Agent with Reflective Search for Automated AI Research
FactGuard: Agentic Video Misinformation Detection via Reinforcement Learning
Stratified GRPO: Handling Structural Heterogeneity in Reinforcement Learning of LLM Search Agents
MFH-NAS:A Hybrid Neural Architecture Search Framework for Multimodal Fusion Object Detection
DexMachina: Functional Retargeting for Bimanual Dexterous Manipulation
Near-Optimal Convergence of Accelerated Gradient Methods under Generalized and $(L_0,L_1)$-Smoothness
Neutral-Reference Prompting for Vision–Language Models
Generalization Bounds for Discrete Diffusion: Statistical Advantage of Masking
Low-Compute Watermark Removal via Dual-Domain Natural Projection
Mind Your Entropy: From Maximum Entropy to Trajectory Entropy-Constrained RL
Beyond Looking Up, Try Looking Around: Harmonizing Global Structure and Local Consistency in Optimal Transport for Short Text Clustering
Amortized Maximum Inner Product Search with Learned Support Functions
Is Generation Required for Data-Efficient Perception?
Information Geometry Loss for Time Series Forecasting
TINNs: Time-Induced Neural Networks for Solving Time-Dependent PDEs
Break the Block: Dynamic-size Reasoning Blocks for Diffusion Large Language Models via Monotonic Entropy Descent with Reinforcement Learning
XSpecMesh: Quality-Preserving Auto-Regressive Mesh Generation Acceleration via Multi-Head Speculative Decoding
Rethinking KV Cache Eviction via a Unified Information-Theoretic Objective
A Probabilistic Framework for LLM-Based Model Discovery
HeraSys: Collaborative Serving of Multiple LLM Workflows via Fine-Grained End-to-End Optimization
Spike-HTR: Spiking Neural Transformer for Handwritten Text Recognition
SG2Loc: Sequential Visual Localization on 3D Scene Graphs
Learning to Label: A Reinforced Self-Evolving Framework for Semi-supervised Referring Expression Segmentation
Distilling Task-Level Coordination Policies for Generalizable Multi-Agent Cooperation
Quantifying the Generalization Gap in Seizure Detection: A Large-Scale Empirical Benchmark via the SzCORE Challenge
SAOT: Self-Supervised Continual Graph Learning with Structure-Aware Optimal Transport
Segment-Aligned Policy Optimization for Multi-Modal Reasoning
Beyond Single-View Indexing: Structure-Aware Multi-View Retrieval for Knowledge-Based VQA
Smoothie: Smoothing Diffusion on Token Embeddings for Text Generation
Equilibrium Propagation for Non-Conservative Systems
TSFAdv: Frequency-Guided Black-Box Adversarial Attacks on Time Series Forecasting
Causes and Consequences of Representational Similarity in Machine Learning Models
Learning Adaptive Topology with FiLM-Guided Distillation for Tertiary Structure-Based RNA Design
Training Prompt Matters: State-Adaptive Optimization for Robust Fine-Tuning
TD-VAD: Breaking Visual Dependence in Video Anomaly Detection with Text-Driven Learning
DuRP: Dual-Stage Physics-Embedded Learning for Joint Radiance and Polarization Restoration
Very Efficient Listwise Multimodal Reranking for Long Documents
On Testing Conditional Mean Independence for Manifold-Valued Data
From Retrieval to Translation: Translating Query into Graph-level Clues for Retrieval-Augmented Generation
A Unified Approach to Interpreting Knowledge Distillation for Large Language Models via Interactions
See, Act, Adapt: Active Perception for Unsupervised Cross-Domain Visual Adaptation via Personalized VLM-Guided Agent
FairMerging: Rethinking Model Merging through the Lens of Fairness
Needles in the Haystack: Addressing Signal Dilution Improves scRNA-seq Perturbation Response Modeling and Evaluation
Exploring More to Solve More: Boosting Diversity in Text Diffusion Models via Entropy-Based Guidance
Enhancing LLMs for Graph Tasks via Graph-aware LoRA Generation
Hyperbolic RQ-VAE enhanced Generative Recommendation with Differential-Length Codebook Strategy
AutoTool: Dynamic Tool Selection and Integration for Agentic Reasoning
QuantumBoost: A lazy, yet fast, quantum algorithm for learning with weak hypotheses
Experience is the Best Teacher: Motivating Effective Exploration in Reinforcement Learning for LLMs
Spatiotemporal Imputation with Graph-Informed Flow Matching
Factored Causal Representation Learning for Robust Reward Modeling in RLHF
Conflict-Aware Additive Guidance for Flow Models under Compositional Rewards
Transolver-3: Scaling Up Transformer Solvers to Industrial-Scale Geometries
Swordsman: Entropy-Driven Adaptive Block Partition for Efficient Diffusion Language Models
Generative Inverse Design with Abstention via Diagonal Flow Matching
Practical and Scalable Hamiltonian Monte Carlo Without the Metropolis Test
DART: Distribution-Aware Adaptive Relational Transfer for Adversarial Attacks against Closed-Source MLLMs
Weasel: Out-of-Domain Generalization for Web Agents via Importance-Diversity Data Selection
KAST-BAR: Knowledge-Anchored Semantically-Dynamic Topology Brain Autoregressive Modeling for Universal Neural Interpretation
Backward SDE–Based Diffusion for Physics-Constrained Generation
Projection-Free Algorithms for Minimax Problems
LoCoT2V-Bench: Benchmarking Long-Form and Complex Text-to-Video Generation
Bridging Your Imagination with Audio-Video Generation via a Unified Director
Steering Beyond the Support: Adversarial Training on Unsupervised Jailbroken Activation Simulation
Leveraging Machine Unlearning for Cost-Efficient Preference Alignment
HE-SNR: Uncovering Latent Logic via Entropy for Guiding Mid-Training on SWE-bench
HyPER: Bridging Exploration and Exploitation for Scalable LLM Reasoning with Hypothesis Path Expansion and Reduction
Discrete Adjoint Schrödinger Bridge Sampler
PrivAct: Internalizing Contextual Privacy Preservation via Multi-Agent Preference Training
Train Once, Reuse Everywhere: Generalizable Implicit ICL by Routing Attention
Constitutional Black-Box Monitoring for Scheming in LLM Agents
Evaluating and Explaining Prompt Sensitivity of LLMs Using Interactions
Hierarchical Anchor Graph Learning for Multi-View Clustering
SEMA: a Scalable and Efficient Mamba like Attention via Token Localization and Averaging
A General Framework for Dynamic Consistent Submodular Maximization
Counterfactual Occlusion-Aware Learning via Visibility Intervention for LiDAR Anomaly Detection
MoRGen: Mixture-of-Resolutions Generative Forecasting for Irregularly Sampled Medical Time-Series Data
MeshTok: Efficient Multi-Scale Tokenization for Scalable PDE Transformers
Active Attacks: Red-teaming LLMs via Adaptive Environments
Multimodal Fact-Level Attribution for Verifiable Reasoning
AnomSeer: Reinforcing Multimodal LLMs to Reason for Time-Series Anomaly Detection
TeamTR: Trust-Region Fine-Tuning for Multi-Agent LLM Coordination
Understanding the Ability of LLMs to Handle Character-Level Perturbation
Mean-Shift PCA by Knockoff Mean
3DGS-HPC: Distractor-free 3D Gaussian Splatting with Hybrid Patch-wise Classification
BOOSTAPR: Boosting Automated Program Repair via Execution-Grounded Reinforcement Learning with Dual Reward Models
FoeGlass: Simple In-Context Learning Is Enough for Red Teaming Audio Deepfake Detectors
Out-of-Distribution Evaluation of Rule-Based and Strategic Reasoning in Chess Transformers
A Provable Expressiveness Hierarchy in Hybrid Linear-Full Attention
ReTabSyn: Realistic Tabular Data Synthesis via Reinforcement Learning
The Cost of Commitment in Option-Based Hierarchical RL
Decouple and Cache: KV Cache Construction for Streaming Video Understanding
Inference-Aware Meta-Alignment of LLMs via Non-Linear GRPO
Latent Forcing: Reordering the Diffusion Trajectory for Pixel-Space Image Generation
OpenMAG: A Comprehensive Benchmark for Multimodal-Attributed Graph
Contractive Anchor Resolvent Diffusion for Incomplete Multi-View Clustering
Incentivized Exploration with Stochastic Covariates: A Two-Stage Mechanism Design for Recommender System
Shrinking the Variance: Shrinkage Baselines for Reinforcement Learning with Verifiable Rewards
Extra-Merge: Tracing the Rank-1 Subspace of Model Merging in Language Model Pre-Training
When Distance Distracts: Representation Distance Bias in BT-Loss for Reward Models
Adaptive Residual-Update Steering for Low-Overhead Hallucination Mitigation in Large Vision-Language Models
Optimal Unconstrained Self-Distillation in Ridge Regression: Strict Improvements, Precise Asymptotics, and One-Shot Tuning
Efficient Online Influence Maximization under the Independent Cascade Model with Node-Level Feedback
Is the Last Layer Sufficient for Uncertainty Quantification?
Last-iterate Convergence of ADMM on Multi-affine Quadratic Equality Constrained Problem
GePBench: Evaluating Fundamental Geometric Perception for Multimodal Large Language Models
Separating Representation from Reconstruction Enables Scalable Text Encoders
XPERT: Expert Knowledge Transfer for Effective Training of Language Models
Flatland: The Adventures of Gradient Descent with Large Step Sizes
AIR-VLA: Vision-Language-Action Systems for Aerial Manipulation
Co-Generative De Novo Functional Protein Design
An Exploration of Non-Euclidean Gradient Descent: Muon and its Many Variants
Toward Effective Multimodal Graph Foundation Model: A Divide-and-Conquer Based Approach
Spiral RoPE: Rotate Your Rotary Positional Embeddings in the 2D Plane
Fast and Accurate Causal Parallel Decoding using Jacobi Forcing
Approximation Theory for Lipschitz Continuous Transformers
Recursive Binding on a Budget: Subspace Carving in Order-$p$ Tensor Memories
Lookahead Unmasking Elicits Reliable Decoding in Diffusion Language Models
The Expressive Power of Low Precision Softmax Transformers with (Summarized) Chain-of-Thought
Adaptive Sharpness-Aware Minimization with a Polyak-type Step size: A Theory-Grounded Scheduler
Streaming Covariate Balancing via Discrepancy-Based Feature Coresets
ShapCCS: Shapley-Driven Client Coreset Selection in Federated Learning
PGT: Procedurally Generated Tasks for improving visual grounding in MLLMs
Robust Sequential Experimental Design for A/B Testing
Item Response Scaling Laws: A Measurement Theory Approach for Efficient and Generalizable Neural Scaling Estimation
SF-Mamba: Rethinking State Space Model for Vision
A Fourier perspective on the learning dynamics of neural networks: from sample complexities to mechanistic insights
Three Years of r/ChatGPT: Societal Impact Evaluations from Social Media Data
DualCOIL: Offline Imitation Learning from Contrasting Demonstrations
Locate then Correct: Debiasing Attention Heads in CLIP
KromHC: Manifold-Constrained Hyper-Connections with Kronecker-Product Residual Matrices
Semi-Supervised Learning for Molecular Graphs via Ensemble Consensus
SCNS: Continual Personalization of Diffusion Models via Submodular Concept Neuron Selection
BlueCodeAgent: A Blue Teaming Agent Powered by Automated Red Teaming for CodeGen AI
A Consensus Anchor-guided Hypergraph Framework for Incomplete Multi-view Clustering
Securing Multi-Agent Systems Against Corruptions via Node Contribution Backpropagation
Greedy Coordinate Diffusion: Effective and Semantically Coherent Adversarial Attacks via Diffusion Guidance
CBV: Clean-label Backdoor Attacks on Vision Language Models via Diffusion Models
Video-MTR: Reinforced Multi-Turn Reasoning for Long Video Understanding
When Is Rank-1 Enough? Geometry-Guided Initialization for Parameter-Efficient Fine-Tuning
On Densest $k$-Subgraph Mining and Diagonal Loading: Optimization Landscape and Finite-Step Exact Convergence Analysis
Model Merging Scaling Laws in Large Language Models
Semantic Cache Distillation: Efficient State Transfer via Reuse and Selective Patching
Approximation of Log-Partition Function in Policy Mirror Descent Induces Implicit Regularization for LLM Post-Training
Conversation for Non-verifiable Learning: Self-Evolving Large Language Models through Meta-Evaluation
WeatherSyn: An Instruction Tuning MLLM For Weather Forecasting Report Generation
FedEMoE: Improving Personalization on Heterogeneous Federated Learning via Elastic Mixture of Experts Architecture
The Role of Target Update Frequencies in Q-Learning
FlowMAP: Flow Matching for Generalizable Agent Planning
Trust Region Inverse Reinforcement Learning: Explicit Dual Ascent using Local Policy Updates
A Perturbation Approach to Unconstrained Linear Bandits
Normalization-equivariant Diffusion Models: Learning Posterior Samplers From Noisy And Partial Measurements
Reranker Helps, but Not Enough: Towards Strong Poisoning Attacks Against Retrieval-Augmented Generation
Robust Inter-Series Dependency Modeling for Time Series Forecasting via Information-Theoretic Alignment
SENDAI: A Hierarchical Sparse-measurement, EfficieNt Data AssImilation Framework
Unsat Core Prediction through Polarity-Aware Representation Learning over Clause-Literal Hypergraphs
DANCE: Dynamic, Available, Neighbor-gated Condensation for Federated Text-Attributed Graphs
CORRECT: COndensed eRror RECognition via knowledge Transfer in multi-agent systems
Beyond Magnitude: Scale-Invariant Evidential Fusion for Multi-View Classification
Clustering as Reasoning: A $k$-Means Interpretation of Chain-of-Thought Graph Learning
Learning-To-Measure: In-Context Active Feature Acquisition
Causal-aware Anomaly Detection for Tabular Data
SMM Transformer: Leveraging Spiking Neural Networks for Multimodal Tasks
Learning High-Frequency Continuous Action Chunks in Latent Space
Rethinking Multimodal Time-Series Forecasting Evaluation
EvoEGF-Mol: Evolving Exponential Geodesic Flow for Structure-based Drug Design
BESplit: Bias-Compensated Split Federated Learning with Evidential Aggregation
MEG-XL: Data-Efficient Brain-to-Text via Long-Context Pre-Training
Sharp Concentration Bounds for Bundle-Valued Statistics on Manifolds
Compositional Planning with Jumpy World Models
Avoid What You Know: Divergent Trajectory Balance for GFlowNets
Who’s in Charge? Disempowerment Patterns in Real-World LLM Usage
Tournament Style RL: Stabilizing Policy Optimization on Non Verifiable Problems
Text-Driven Fusion for Infrared and Visible Images: Achieving Image Scene Adaptation on Hyperbolic Space
CODiff: One-Step Diffusion Model for Camouflaged Object Detection
Neural–Evolutionary Symbolic Regression with Global Constraints: Constraint-Aware Decoding and Reward Shaping
Minimizing Upper Confidence Bounds: A Data-Driven Framework for Stochastic Programming
Learning Discriminative and Generalizable Anomaly Detector for Dynamic Graph with Limited Supervision
Affine-Equivariant Kernel Space Encoding for NeRF Editing
RefineEvo: Planning-Guided Heuristic Evolution with Bidirectional Experience
Next-Token Prediction and Regret Minimization
Bridge Matching Sampler: Scalable Sampling via Generalized Fixed-Point Diffusion Matching
FreeText: Training-Free Text Rendering via Attention Localization and Spectral Glyph Injection
Mind the Gap: Catching Hallucinations via Evidence Drop on the Reasoning Manifold
MAC-NeRF: Motion-Aware Curriculum Learning for Dynamic LiDAR NeRFs
Equalized Generative Treatment: Matching f-divergences for Fairness in Generative Models
Harnessing Spectrum Video for Subject-Level Few-Shot and Cross-Montage EEG Generalization
mmBERT: A Modern Multilingual Encoder with Annealed Language Learning
Tight Margin-Based Generalization Bounds for Voting Classifiers over Finite Hypothesis Sets
Co-Evolving Latent Action World Models
Towards Uniformity and Alignment for Multimodal Representation Learning
scChord: A Probabilistic Manifold Rectification Framework for RNA-to-Protein Translation
Concept Heterogeneity-aware Representation Steering
Budget-Efficient Attacks and Robustness Training for Cooperative MARL
Omitted Variable Bias in Language Models Under Distribution Shift
MultiHal: Multilingual Dataset for Knowledge-Graph Grounded Evaluation of LLM Hallucinations
Anchoring Self-Play for Code Repair
Large Language Model Agents Are Not Always Faithful Self-Evolvers
Equivariant Covariance Tensors: Guaranteed SPD Uncertainty for Tensor-Valued Geometric Learning
Towards the Training of Deeper Predictive Coding Neural Networks
From Internal Diagnosis to External Auditing: A VLM-Driven Paradigm for Data-Free Online Backdoor Defense
Vision Transformer Finetuning Benefits from Non-Smooth Components
Sharp description of local minima in the loss landscape of high-dimensional two-layer ReLU neural networks
Focus, Align, and Sustain: Counteracting Gradient Dilution in Incremental Object Detection
PowerFlow: Unlocking the Dual Nature of LLMs via Principled Distribution Matching
Dual-branch Robust Unlearnable Examples
Editable Proof Sketch for Automated Theorem Proving
Neuromem: A Granular Decomposition of the Streaming Lifecycle in External Memory for LLMs
Fast Byte Latent Transformer
LATO: 3D Mesh Flow Matching with Structured TOpology Preserving LAtents
FormAct: Agentic Source Editing for Rich-Format Document Generation
VELR: Efficient Video Reward Feedback via Ensemble Latent Reward Models
AgentVocab: Structure-Aware Vocabulary Adaptation for Efficient LLM Agents
LLM-Guided Communication for Cooperative Multi-Agent Reinforcement Learning
Dual-stage Contrastive Learning-enhanced Multi-view Variational Clustering
SOLAR: Self-supervised Joint Learning for Symmetric Multimodal Retrieval
Hard labels sampled from sparse targets mislead rotation invariant algorithms
NeuroCLUS: A Foundation Model with Functional Clustering for Intracranial Neural Decoding
Investigating Advanced Reasoning of Large Language Models via Black-Box Environment Interaction
Boost the Identity-Preserving Embedding for Consistent Visual Generation
Adaptive Visual Autoregressive Acceleration via Dual-Linkage Entropy Analysis
M-IDoL: Information Decomposition for Modality-Specific and Diverse Representation Learning in Medical Foundation Model
Memory-Efficient LLM Pretraining via Minimalist Optimizer Design
LLM4Cov: Execution-Aware Agentic Learning for High-coverage Testbench Generation
Distribution-Calibrated Inference Time Compute for Thinking LLM-as-a-Judge
Embodied Task Planning via Graph-Informed Action Generation with Large Language Models
Vision-aligned Latent Reasoning for Multi-modal Large Language Model
DREAM: Dual-Standard Semantic Homogeneity with Dynamic Optimization for Graph Learning with Label Noise
MINIM: Privacy-Aware Minimal View for Agents via Trusted Local Sanitization
Distribution Matching Variational AutoEncoder
Bits That Count: Quantifying and Predicting Capabilities of Language Models
Twice Sequential Monte Carlo for Tree Search
Amortized Simulation-Based Inference in Generalized Bayes via Neural Posterior Estimation
General Covariant Action Modeling: Constructing Generalized Manifolds via Spatio-Temporal Decoupling
Closing the Sim-to-Real Gap in Non-Markovian Spreading Processes via GPU-Accelerated Distributional RL
Instance-Specific Approximation Ratios for Correlation Clustering and Max-Cut
VIA-SD: Verification via Intra-Model Routing for Speculative Decoding
ExpAlign: Expectation-Guided Vision–Language Alignment for Open-Vocabulary Grounding
Learn from Your Mistakes: Tree-like Self-Play for Secure Code LLMs
Revealing Behavioral Plasticity in Large Language Models: A Token-Conditional Perspective
Personalized Image Generation via Human-in-the-loop Bayesian Optimization
PCA of Probability Measures: Sparse and Dense Sampling Regimes
Efficient Inference for Noisy LLM-as-a-Judge Evaluation
Blocking the Leakage: Manifold-Aware Gradient Projection for Long-Horizon Test-Time Adaptation
Thinned Mean Field Langevin Dynamics
Self-Augmenting Retrieval for Diffusion Language Models
MMClima: A Framework for Multimodal Climate Science Data and Evaluation
Spectral Gradient Descent Mitigates Anisotropy-Driven Misalignment: A Case Study in Phase Retrieval
A Theory of Data Acquisition and Pricing at Scale
Toward Safe Quantization-Aware Fine-tuning: Understanding and Mitigating Safety Alignment Degradation
CORE-MTL: Rethinking Gradient Balancing via Causal Orthogonal Representations
Joint Model and Data Sparsification via the Marginal Likelihood
Evaluating AI Grading on Real-World Handwritten College Mathematics: A Large-Scale Study Toward a Benchmark
The Devil is in the Condition Numbers: Why is GLU Better than non-GLU Structure?
FiGuRO: Intrinsic Dimension Estimation for Multi-Modal Data
SpeedVFI: One-step Diffusion for Efficient Video Frame Interpolation
Drop-in Circulant Structural Priors for Transformer Decoding of Cyclic Codes
Global Merger-Arbitrage Forecasting with Language Models
GuidedBridge: Training-freely Improving Bridge Models with Prior Guidance
Who Gets Credit or Blame? Attributing Accountability in Modern AI Systems
GenUnfold: Rapidly Predict Protein Mechanical Unfolding Trajectory via a Physics-Guided Diffusion Model
Improved Distribution Estimation in $\ell_\infty$
MOC: Multi-Order Communication in LLM-based Multi-Agent Systems
PSMix: Robust Point Cloud Recognition through Spectral Domain Mixing
Normalized Rewards for Preference Optimization
Federated Manifold Learning (FML): Tackling Domain Heterogeneity with Structural Knowledge Transfer
SCOUT: Cyclic Causal Discovery Under Soft Interventions with Unknown Targets
Deep Incentive Design with Differentiable Equilibrium Blocks
A Judge-Aware Ranking Framework for Evaluating Large Language Models without Ground Truth
GeoAlign: Geometric Rollout Curation for Robust LLM Reinforcement Learning
Unfolding Generative Flows with Koopman Operators: Trajectory-Preserving Linearization
Robust Cross-Modal Retrieval via Generative Semantic Refinement and Exclusion-Guided Adaptation
Meta-iLaD: Identifiable Latent Dynamics via Meta-Learning of Dynamics Environments
When LLMs Encounter Open-world Graph Learning: A Fresh View on Unlabeled Data Uncertainty
Mitigating Translationese Bias in Multilingual LLM-as-a-Judge via Disentangled Information Bottleneck
AGoQ: Activation and Gradient Quantization for Memory-Efficient Distributed Training of LLMs
Di-BiLPS: Denoising induced Bidirectional Latent-PDE-Solver under Sparse Observations
Failure is Feedback: History-Aware Backtracking for Agentic Traversal in Multimodal Graphs
No Free Lunch: Non-Asymptotic Analysis of Prediction-Powered Inference
When Embedding-Based Defenses Fail: Rethinking Safety in LLM-Based Multi-Agent Systems
LLMs as Noisy Channels: A Shannon Perspective on Model Capacity and Scaling Laws
Spectral Collapse Drives Loss of Plasticity in Deep Continual Learning
Attention's forward pass and Frank-Wolfe
DynaSchedBench: Calibrated Dynamic Scheduling Benchmarks and Observability Paradox in LLM-based Scheduling Agents
The Forgetting-Retention Dilemma: Certified Unlearning Theory in Continual Learning
Estimating Continuous Treatment Effects with Two-Stage Kernel Ridge Regression
AGZO: Activation-Guided Zeroth-Order Optimization for LLM Fine-Tuning
Condition-Aware Graph Flow Matching for Modeling the Distributions of Complex Fluid Systems
Flat Minima and Generalization: Insights from Stochastic Convex Optimization
Target-Agnostic Calibration under Distribution Shift with Frequency-Aware Gradient Rectification
Textual Stochastic Gradient Descent: Discrete Optimization of External Memory for Reasoning Language Agents
Efficient Multi-Agent Reasoning via Confidence-Guided Adaptive Debate
From Generative to Episodic: Sample-Efficient Replicable Reinforcement Learning
Learning Multi-Timescale Abstractions for Hierarchical Combinatorial Planning
Memora: A Harmonic Memory Representation Balancing Abstraction and Specificity
LEGO: An LLM-Enabled Hierarchical Optimizer for Tensor Computation Graphs with Structure-Aware Search and Compositional Synthesis
One Probe Won’t Catch Them All: Towards Targeted Deception Detection
Latent Spherical Flow Policy for Reinforcement Learning with Combinatorial Actions
Learning to Emulate Chaos: Adversarial Optimal Transport Regularization
From Generalist to Specialist Representation
SiameseNorm: Breaking the Barrier to Reconciling Pre/Post-Norm
CAReDiO: Enhancing Cultural Alignment of LLM via Representativeness and Distinctiveness Guided Data Optimization
T$^2$PO: Uncertainty-Guided Exploration Control for Stable Multi-Turn Agentic Reinforcement Learning
Learning to Refine: Spectral-Decoupled Iterative Refinement Framework for Precipitation Nowcasting
Towards Understanding Modality Interaction in Multimodal Language Models via Partial Information Decomposition
Bayesian-LoRA: Probabilistic Low-Rank Adaptation of Large Language Models
Learning Biophysical Models of Large-Scale Multineuronal Data To Enable Precise Neurostimulation
Human-AI Collaborative Uncertainty Quantification
More Capable, Less Cooperative? When LLMs Fail at Zero-Cost Collaboration
Chunk-Guided Q-Learning
LLM-Guided Loop Bound Generation for Program Termination Verification
Step-Size Stability in Stochastic Optimization: A Theoretical Perspective
Width Independent Bounds for the Local Lipschitz Constant of Deep Neural Networks at Random Initialization and after Lazy Training
FedTreeLoRA: Reconciling Statistical and Functional Heterogeneity in Federated LoRA Fine-Tuning
Taming the Loss Landscape of PINNs with Noisy Feynman–Kac Supervision: Operator Preconditioning and Non-Asymptotic Error Bounds
From Lyapunov Analysis to Algorithm Design in two-sided PL Minimax Optimization
From Feasible to Practical: Pareto-Optimal Synthesis Planning
Don't Walk the Line: Boundary Guidance for Filtered Generation
Identifying Learnwares via Reduced Neural Conditional Mean Embedding
Grouter: Decoupling Routing from Representation for Accelerated MoE Training
Generalized Discrete Diffusion with Self-Correction
Improved Scaling Laws via Weak-to-Strong Generalization in Random Features Ridge Regression
Foreground-Aware Token Routing Vision Transformer for Real-Time Satellite Video Tracking
Unsupervised Diffusion Solver for Combinatorial Optimization via Combinatorial Adjoint Matching
Causal Discovery for Irregularly Time Series with Consistency Guarantees
The Geometry of Projection Heads: Conditioning, Invariance, and Collapse
Mining Useful General Data for Low-Resource Domain Adaptation
SWE-IF: Aligning Code Evaluation with Human Preference
QPoint: End-to-End Lightweight Point Cloud Processing via Robust Quaternion Feature Learning
Efficient numeracy in language models through single-token number embeddings
Neural Low-Discrepancy Sequences
Physics from Video: Identifiability of Time-Invariant Second-Order ODEs under Minimal Trajectory Conditions
Tail Annealing for Heavy-Tailed Flow Matching
Optimal Top-$k$ Identification from Pairwise Comparisons
Causal Identification from Counterfactual Data: Completeness and Bounding Results
SynLaD: Latent Diffusion for Generating Synthesizable Molecules Conditioned on 3D Pharmacophore Profiles
Ariadne's Thread of LipSync: Unraveling Forgeries via Inconsistency between Lip Motions and Head Poses
Rethinking 1-bit Optimization Leveraging Pre-trained Large Language Models
Doubly Regularized Markov Decision Processes for Robust Reinforcement Learning
DIYHealth Suite: Dataset, Model, and Benchmark for Health Management at Home
High-Probability Convergence Guarantees of Decentralized SGD
The Cost of Learning Under Multiple Change Points
Baguan-TS: dual in-context learning model for time series forecasting with covariates
AdaRoPE: Not All Attention Heads Should Rotate and Scale Equally
CoF-T2I: Video Models as Pure Visual Reasoners for Text-to-Image Generation
Does Your Reasoning Model Implicitly Know When to Stop Thinking?
Consistency Training Can Entrench Misalignment
Strategy-Aware Optimization Modeling with Reasoning LLMs
SlideSparse: Fast and Flexible (2N-2):2N Structured Sparsity
PODiff: Latent Diffusion in Proper Orthogonal Decomposition Space for Scientific Super-Resolution
CLIP Tricks You: Training-free Token Pruning for Efficient Pixel Grounding in Large Vision-Language Models
Towards Whole-corpus Reconstruction of Heterogeneous RAG Knowledge Bases
Distortion of AI Alignment Revisited: RLHF is a Decent Utilitarian Aligner
Real-Time Aligned Reward Model beyond Semantics
EAKV: An Entropy-Driven Adaptive KV Compression Framework for Long Video Understanding
PromptDyG: Test-Time Prompt Adaptation on Dynamic Graphs
Causal Disentangled Anchor Learning for Scalable Fair Multi-view Clustering
Automatically Finding Reward Model Biases
The Perception–Physics Paradox: Probing Scientific Alignment with TC-Bench
ProjQ: Project-and-Quantize for Adapter-Aware LLM Compression
Leveraging Lineage Barcodes as Natural Augmentations for Contrastive Learning of Cell Fate in scRNA-seq Data
Rethinking Loss Reweighting for Imbalance Learning as an Inverse Problem: A Neural Collapse Point of View
Interpreting and Enhancing Emotional Circuits in Large Vision-Language Models via Cross-Modal Information Flow
EpiTwin: Spatiotemporal Graph Transformers for Epileptic sEEG Signal Reconstruction
Less is Enough: Synthesizing Diverse Data in Feature Space of LLMs
Inference-time Alignment with Rewards in Besov Spaces: Provable Advantages of Feature Learning and Multi-Step Policy Updates
Segment-driven Structural Induction and Semantic Alignment for Heterogeneous Tabular Representation
Fast and Near-Optimal Algorithms for Private Hypothesis Selection
Understanding Truncated Positional Encodings for Graph Neural Networks
Unlocking Zero-Shot Geospatial Reasoning via Indirect Rewards
Learning to Remember, Learn, and Forget in Attention-Based Models
Stage-wise Distortion–Perception Traversal in Zero-shot Inverse Problems with Diffusion Models
On the Effect of Misspecifying the Embedding Dimension in Low-rank Network Models
Uncovering Hidden Triggers: Backdoor Attribution in Language Models
AURA: Visually Interpretable Affective Understanding via Robust Archetypes
Position: Stop evaluating AI with human tests, develop principled, AI-specific tests instead
DRIFT-BENCH: Diagnosing CoopeRative Breakdowns in LLM Agents under Input Faults via Multi-Turn Interaction
ZeroUnlearn: Few-Shot Knowledge Unlearning in Large Language Models
Allocating Variance to Maximize Expectation
Cutting LLM Evaluation Costs with SySRs: A Bandit Algorithm That Provably Exploits Model Similarity
Vegas: Self-Speculative Decoding with Verification-Guided Sparse Attention
Active Learning with Foundation Model Priors: Efficient Learning under Class Imbalance
Tiny Brains, Giant Impact: Uncovering the Keystone Neurons of LLM with Just a Few Prompts
Position: AI Researchers Must Lead Arms Control to Mitigate Military AI Risks
Med-SegLens: Latent-Level Model Diffing for Interpretable Medical Image Segmentation
Hyperbolic Neural Operator
Position: Every Ground Truth is a Human Construction, not an Objective Truth
Optimal Transport–Guided Stochastic Control for Graph Combinatorial Optimization
Conditional Coverage Diagnostics for Conformal Prediction
SSL4RL: Revisiting Self-supervised Learning as Intrinsic Reward for Visual-Language Reasoning
Optimal conversion from Rényi Differential Privacy to $f$-Differential Privacy
VideoFlexTok: Flexible-Length Coarse-to-Fine Video Tokenization
HiMe: Hierarchical Embodied Memory for Long-Horizon Vision-Language-Action Control
Induction Meets Biology: Mechanisms of Repeat Detection in Protein Language Models
AnyMod-LLVE: Low-Light Video Enhancement with Modality-Agnostic Inference
APIC: Orthogonalized Neuro-Symbolic Modeling for Nonlinear Dissipative Dynamics
PRISM: Demystifying Retention and Interaction in Mid-Training
Preserving Plasticity in Continual Learning via Dynamical Isometry
EPSVec: Efficient and Private Synthetic Data Generation via Dataset Vectors
Symbal: Detecting Systematic Misalignments in Model-Generated Captions
Revisiting Uncertainty: On Evidential Learning for Partially Relevant Video Retrieval
EEG-FM-Bench: A Comprehensive Benchmark for the Systematic Evaluation and Diagnostic Analyses of EEG Foundation Models
SoftMoE: Soft Differentiable Routing for Mixture-of-Experts in LLMs
Evidential Copula Concept Embedding Models
HiDe: Rethinking The Zoom-IN method in High Resolution MLLMs via Hierarchical Decoupling
Bridging Functional Correctness and Runtime Efficiency Gaps in LLM-Based Code Translation
TokenSwap: Backdoor Attack on the Compositional Understanding of Large Vision-Language Models
Bridging the Perceptual Gap: Residual-Enhanced Downscaling and Manifold-Aware Perception Alignment Adaptation for NR-IQA
TEFormer: Structured Bidirectional Temporal Enhancement Modeling in Spiking Transformers
Revisiting the Platonic Representation Hypothesis: An Aristotelian View
Optimal Attention Temperature Improves the Robustness of In-Context Learning under Distribution Shift in High Dimensions
Chebyshev Policies and the Mountain Car Problem: Reinforcement Learning for Low-dimensional Control Tasks
Concept-Guided Tokenization: Closing the Gap Between Reconstruction and Generation
The Truth Stays in the Family: Enhancing Contextual Truthfulness via Inherited Heads in Model Lineages
Linear Bandits beyond Inner Product Spaces, the case of Bandit Optimal Transport
A-MemGuard: A Proactive Defense Framework For LLM-Based Agent Memory
Generation Enhances Understanding in Unified Multimodal Models via Multi-Representation Generation
Ranking Free RAG: Replacing Re-ranking with Selection in RAG for Sensitive Domains
Position: Neglecting the Sustainability of AI is Fuelling a Global AI Arms Race
Emergent Communication Under Misinformation
CoT is Not the Chain of Truth: An Empirical Internal Analysis of Reasoning LLMs for Fake News Generation
Higher-Order Certified Robustness for Regression
Rethinking Code Complexity Through the Lens of Large Language Models
Learning-augmented Rent-or-Buy with a Sample
LUGS: Latent-aware Guidance for Efficient Unmasking in Diffusion Large Language Models
Position: Deployed Reinforcement Learning should be Continual
Diagnosing Multi-step Reasoning Failures in Black-box LLMs via Stepwise Confidence Attribution
Continual Segmentation under Joint Nonstationarity
Multilingual Safety Alignment Via Sparse Weight Editing
Rethinking the Hardness of PbRL: A Provable General Regret Bound
From Diagrams to Code: Multilingual Programming with Visual Design
Error Analysis of Discrete Flow with Generator Matching
Path-conditioned training: a principled way to rescale ReLU neural networks
SetPO: Set-Level Policy Optimization for Diversity-Preserving LLM Reasoning
Interpretability Transfer from Language to Vision via Sparse Autoencoders
PhaseCoder: Microphone Geometry-Agnostic Spatial Audio Understanding for Multimodal LLMs
SciVideoBench: Benchmarking Scientific Video Reasoning in Large Multimodal Models
Principled RL for Flow Matching Emerges from the Chunk-level Policy Optimization
MASPOB: Bandit-Based Prompt Optimization for Multi-Agent Systems with Graph Neural Networks
video-SALMONN S: Memory-Enhanced Streaming Audio-Visual LLM
SAGE: Shaping Anchors for Guided Exploration in RLVR of LLMs
Aggregate Models, Not Explanations: Improving Feature Importance Estimation
The Differences Between Direct Alignment Algorithms are a Blur
Group Cognition Learning: Making Everything Better Through Controlled Two-Stage Agents Collaboration
How do LLMs Compute Verbal Confidence?
Clipping Low-Probability Tokens in SFT Yields a Generalizable Initialization for RL
Learning Robust Multi-Agent Policies via Selective Adversarial Fault Induction
iGRPO: Fast Online RL for Flow Matching Model with Instant Reward
Extending Prediction-Powered Inference through Conformal Prediction
Finding Differentially Private Second Order Stationary Points in Stochastic Minimax Optimization
Nonlinear Covariate Balance in Experimental Design
Off-Policy Learning in Large Action Spaces: Optimization Matters More Than Estimation
Edge-colored Clustering in Hypergraphs: A MaxECC Approximation
Dynamic Thinking-Token Selection for Efficient Reasoning in Large Reasoning Models
Modeling Spectral Energy Shifts in Spatio-Temporal Graph Anomaly Detection
Language Generation with Replay: A Learning-Theoretic View of Model Collapse
Identifying and Mitigating Errors in Gradient Aggregation of Distributed Data Parallel Training
From Reasoning Traces to Reusable Modules: Understanding Compositional Generalization in Language Model Reasoning
Causally Evaluating the Learnability of Formal Language Tasks
Furina: Fragmented Uncertainty-Driven Refusal Instability Attack
Don't Overthink with Pixels: Efficient Reasoning for Segmentation
Optimal Self-Consistency for Efficient Reasoning with Large Language Models
Revisiting Regularized Policy Optimization for Stable and Efficient Reinforcement Learning in Two-Player Games
SLIM: Secure and Efficient Inference for Large Language Models on Untrusted Devices via TEEs
Syntax vs. Semantics: How Transformers Learn Deep Dependencies
Mitigating Mask Prior Drift and Positional Attention Collapse in Large Diffusion Vision-Language Models
SEM-CTRL: Semantically Controlled Decoding
From Reward-Free Representations to Preferences: Rethinking Offline Preference-Based Reinforcement Learning
Saving Foundation Flow-Matching Priors for Inverse Problems
Attention Projection Mixing with Exogenous Anchors
Robust In-Context Reinforcement Learning Under Reward Poisoning Attacks
Zeroth-Order Optimization at the Edge of Stability
Towards Feedback-to-Plan Decisions for Self-Evolving LLM Agents in CUDA Kernel Generation
Ramba: Selective State-Space Models for Relational Deep Learning
Revisiting Parameter-Based Knowledge Editing in Large Language Models: Theoretical Limits and Empirical Evidence
Group Distributionally Robust Optimization-Driven RL for LLM Reasoning
Learning Randomized Reductions
Transformers Provably Learn Algorithmic Solutions for Graph Connectivity, But Only with the Right Data
Real-Time Monitoring and Calibration of Chain-of-Thought Sycophancy in Large Reasoning Models
Partial Identification under High-Dimensional Potential Outcomes and Confounders via Optimal Transport
Emergent Visual Representations through Unsupervised Spiking Networks with Synaptic Pruning
Identifying and Correcting Label Noise for Robust GNNs via Influence Contradiction
Non-Euclidean Gradient Descent Operates at the Edge of Stability
Goal-Conditioned Agents that Learn Everything All at Once
Singular Bayesian Neural Networks
DRIFT: Decoupled Rollouts and Importance-Weighted Fine-Tuning for Efficient Multi-Turn Optimization
DTS: Enhancing Large Reasoning Models via Decoding Tree Sketching
WET: Mitigating World-Conditioned Knowledge Conflicts via World Entropy Tethering
Words & Weights: Streamlining Multi-Turn Interactions via Co-Adaptation
RouterInterp: Understanding Superposed Specialisation in Mixture of Experts Routing
Non-Parametric Optimization for Scalable Learning in Stochastic Decision Problems
E²I-VRWKV: Explicit EPI-Representation and Interaction-Aware Vision-RWKV for Light Field Semantic Segmentation
From Seeing to Thinking: Decoupling Perception and Reasoning Improves Post-Training of Vision-Language Models
Precision-Induced Miscalibration: Understanding and Correcting Confidence Distortion in Quantized Neural Networks
Approximating Drift-Diffusion Models for User Decisions under Nudging and External Information
On the Convergence of Decentralized Stochastic Minimax Optimization Algorithm with Compressed Communication
EasyBalance: Cross-Layer Load Balancing in Distributed MoE Inference
Krause Synchronization Transformers
Lookahead Sample Reward Guidance for Test-Time Scaling of Diffusion Models
End-to-End Autoregressive Image Generation with 1D Semantic Tokenizer
Hydra-Nav: Object Navigation via Adaptive Dual-Process Reasoning
Cross-Modal Knowledge Distillation without Paired Data: Theoretical Foundation and Algorithm
Detecting the Semantic Fixed Point: A Geometric Framework for Efficient Inference
GeoFlow: Geo-Aware Modeling of Inter-Area Relationships in Origin-Destination Flow Prediction and Generation
Nested birth-death processes are competitive with neural networks as time-dependent models of protein evolution
Physics-Guided Motion Loss for Video Generation Model
An Exterior Method for Nonnegative Matrix Factorization
LoBCD-GW: A Fast and Data-Dependent Algorithm for Computing Gromov-Wasserstein Distance via Localized Block Coordinate Descent
Learning Generalizable Skill Policy with Data-Efficient Unsupervised RL
MetaPerch: Learning from metadata for bioacoustics foundation models
Instance-Level Costs for Nuanced Classifier Evaluation
Riemannian Diffusion Models on General Manifolds via Physics-Informed Neural Networks
LatentLens: Revealing Highly Interpretable Visual Tokens in LLMs
Multi-Label Test-Time Adaptation with Bayesian Conditional Priors
Bayesian Tensor Decomposition with Diffusion Model Prior
TestExplora: Benchmarking LLMs for Proactive Bug Discovery via Repository-Level Test Generation
StreamFlow: Theory, Algorithm, and Implementation for High-Efficiency Rectified Flow Generation
Towards the Explainability of Temporal Graph Networks via Memory Backtracking and Topological Attribution
Causal Representation Learning with Optimal Compression and Complex Treatments
Stochastic Sparse Attention for Memory-Bound Inference
Large Vision-Language Models Get Lost in Attention
Towards Parameter-Free Temporal Difference Learning
BFCL Audio: An Audio Function Calling Evaluation for Large Language Models
ORBIT: A Prognostic World Model for Ocular Reasoning Based on Imagined Trajectories
On the Anisotropy of Score-Based Generative Models
On the Identifiability of Poisson Branching Structural Causal Model Under Latent Confounding
FOVI: A biologically-inspired foveated interface for deep vision models
Mitigating Plasticity Loss through Architectural Design in Continual Learning
Learning syntax without semantics: Disentangled tiny language models
RetrOrchestrator: A Multi-Step Retrosynthesis Agent Dynamically Orchestrating Single-Step Transition Models
The Hidden Risk: Membership Inference Attacks on Multimodal Federated Learning via Modality Imbalance
Frequentist Consistency of Prior-Data Fitted Networks for Causal Inference
Geodesic Flow Matching for Denoising High-Dimensional Structured Representations
Learn from A Rationalist: Distilling Intermediate Interpretable Rationales
Learning Anisotropic Value Geometry with Finsler Reinforcement Learning
Role-Level Inductive Bias for Cross-Task Generalization in Multi-Agent Reinforcement Learning
Enhanced Latent-Space Adversarial Training for Super-Resolution
MORE: A Multilingual Document Parsing Benchmark and Evaluation
On the Intrinsic Limits of Transformer Image Embeddings in Non-Solvable Spatial Reasoning
Approximation Bounds for Transformer Networks with Application to Regression
Distributional Alignment Games for Answer-Level Fine-Tuning
Sharp Empirical Bernstein Inequalities for the Variance of Bounded Random Variables
VJEPA: Variational Joint Embedding Predictive Architectures as Probabilistic World Models
InvGNN: Learning Invertible Node Representations on Graphs
$\mathcal{O}(\log N)$ Latent Dimension Suffices for Universal Approximation of Permutation-invariant Function
Geometrically Constrained Outlier Synthesis
When Does Predictive Inverse Dynamics Outperform Behavior Cloning?
A recipe for scalable attention-based ML potentials: unlocking long-range accuracy with all-to-all node attention
Branching Diffusion for Point Processes in Time and Space
TwinWeaver: An LLM-Based Foundation Model Framework for Pan-Cancer Digital Twins
Explainable Forensics of Manipulated Segments in Untrimmed Long Videos
The Relative Instability of Model Comparison with Cross-validation
Probing the Geometry of Diffusion Models with the String Method
Rethinking 3D Shape Generation: Diffusion over Superquadrics
Joint Navigation and Manipulation Planning with 3D Interaction Chains
CausalX: A Unified and Causally-Interpretable Plug-and-Play Model for Multi-modal Spatio-Temporal Forecasting
Eating for a Sustainable Planet: Personalized Sustainable Diet Recommendation via Constraint-Aware Decision-Making Modeling
CapBencher: Give Your LLM Benchmark a Built-in Alarm for Test-Set Overfitting
G-RANS: Generalizable Residual-Aware Neural Solvers for Sparse Systems
HSMAD: Heterophily-Driven Spectral and Manifold Learning for Graph Anomaly Detection
SimpleMem: Efficient Lifelong Memory for LLM Agents
Density-Guided Robust Counterfactual Explanations on Tabular Data under Model Multiplicity
CryoACE: An Atom-centric Framework for Accurate and Automated Model Building in Cryo-EM
InfoFlow KV: Information-Flow-Aware KV Recomputation for Long Context
CLASP: Online learning algorithms for Convex Losses And Squared Penalties
OPIC: Enhancing Language Model Merging via Optimizing In-Context Capability
Margin-Adaptive Confidence Ranking for Reliable LLM Judgement
Query-Based Asymmetric Modeling with Decoupled Input–Output Rates for Speech Restoration
Adaptive Recurrent Message Passing for Test Time Computing on Graphs
Beyond Rational Illusion: Behaviorally Realistic Strategic Classification
Langevin Rollout Optimization for Modelic Reinforcement Learning
Pushing the Limits of Block Rotations in Post-Training Quantization
Online Compatible Reward Identification from Preference Feedback
EchoAttention: Exploiting Token-Pair Redundancy and Frame-Block Similarity for Efficient Video Generation
Trajectory-Aware Spiking DiTs Conversion via Membrane Potential Error-Feedback
TreePO: Enhancing Policy Efficacy and Inference Efficiency with Tree Modeling
QuITE: Query-Based Irregular Time Series Embedding
Class-Grouped Normalized Momentum and Faster Hyperparameter Exploration to Tackle Class Imbalance in Federated Learning
TelecomTS: A Multi-Modal Observability Dataset for Time Series and Language Analysis
Seeing Without Understanding: Disentangling Perception, Reasoning, and Simulation in VLM Gameplay
SAEs-BrainMap: Unveiling the Emergence of Specialized Concepts in Deep Models via Brain Alignment
Reward Modeling from Natural Language Human Feedback
Planar Symmetric Pattern Generation
TT-Sparse: Learning Sparse Rule Models with Differentiable Truth Tables
Unveiling Prior-Data Fitted Networks on Causal Effect Estimation: Pre-Training or Fine-Tuning?
Language as a Wave Phenomenon: Semantic Phase Locking and Interference in Neural Networks
Weights to Code: Extracting Interpretable Algorithms from the Discrete Transformer
POET-X: Memory-efficient LLM Training by Scaling Orthogonal Transformation
Learning Disentangled Multi-Agent World Model for Decentralized Control
Ophiuchus: Incentivizing Tool-augmented ''Think with Images'' for Joint Medical Segmentation, Understanding and Reasoning
VBA: Vector Bundle Attention for Intrinsically Geometric Representation Learning
Convex Distance Operator Transport: A Convex and Geometry-Preserving Formulation
ECSEL: Explainable Classification via Signomial Equation Learning
RSAgent: Learning to Reason and Act via Multi-Turn Tool Invocations for Text-Guided Segmentation
Evaluating LLMs When They Do Not Know the Answer: Statistical Evaluation of Mathematical Reasoning via Comparative Signals
Why ReLU? A Bit-Model Dichotomy for Deep Network Training
Revisiting OOD Generalization in Programmatic RL
TabMGP: Martingale Posterior with TabPFN
Looking Locally: Object-Centric Vision Transformers as Foundation Models for Efficient Segmentation
Benchmarking and Improving Fine-Grained Text-to-Image Alignment via Paired Reinforcement Learning
G$^2$RPO: Geometric GRPO; Escaping LLM's Reasoning Rut to Break Accuracy--Entropy Trade-off
AutoNumerics-Zero: Automated Discovery of State-of-the-Art Mathematical Functions
Referring Multiple Regions with Large Multimodal Models via Contextual Latent Steering
On the Spectral Unreachability of Brain Graph Learning
Shifting the Breaking Point of Flow Matching for Multi-Instance Editing
Star Elastic: Many-in-One Reasoning LLMs with Efficient Budget Control
Training Language Model Agents to Find Vulnerabilities with CTF-Dojo
Networked Information Aggregation for Binary Classification
Conf-Gen: Conformal Uncertainty Quantification for Generative Models
On the Generalization Gap in Self-Evolving Language Model Reasoning
SSA: Sparse Sparse Attention by Aligning Full and Sparse Attention Outputs in Feature Space
Towards Unified Multimodal Pretraining
UI2Code^N: UI-to-Code Generation as Interactive Visual Optimization
ConceptMoE: Adaptive Token-to-Concept Compression for Implicit Compute Allocation
Are Large Reasoning Models Interruptible?
Toward Identifiable Sparse Autoencoders
Hermes: An Evidence-Driven Agentic Framework for Trustworthy and Explainable AI-Generated Video Detection
VisionWebDev: A Hierarchical Benchmark for Visual Website Development with Agent Verification
STABLEVAL: Disagreement-Aware and Stable Evaluation of AI Systems
What Makes Value Learning Efficient in Residual Reinforcement Learning?
PSG-Nav: Probabilistic Scene Graph Navigation via Multiverse Decision Making
Trading Complexity for Expressivity Through Structured Generalized Linear Token Mixing
GAAVI: Global Asymptotic Anytime Valid Inference for the Conditional Mean Function
LUVE : Latent-Cascaded Ultra-High-Resolution Video Generation with Dual Frequency Experts
Approximation Error Upper and Lower Bounds for Hölder Class with Transformers
Metric—Phase Fields: Decoupling Distance and Sign for Thin-Structure Reconstruction from Unoriented Point Clouds
AOEB: Benchmarking Agent-Oriented Multimodal Embeddings
OneSearch: A Preliminary Exploration of the Unified End-to-End Generative Framework for E-commerce Search
ReasonEdit: Editing Vision--Language Models using Human Reasoning
Modeling Covariate Transition for Efficient Estimation of Longitudinal Treatment Effects in Randomized Experiments
DGG-HMR: Multi-Person Human Mesh Recovery with Depth-Guided Geometric Anchoring
Deep networks learn to parse uniform-depth context-free languages from local statistics
3DGS$^2$-TR: A Scalable Second-Order Trust-Region Method for 3D Gaussian Splatting
MIRO: MultI-Reward cOnditioned pretraining improves T2I quality and efficiency
Dataset Distillation Efficiently Encodes Low-Dimensional Representations from Gradient-Based Learning of Non-Linear Tasks
Spatial Priors via Space Filling Curves for Small and Limited Data Vision Transformers
Categorical Reparameterization with Denoising Diffusion Models
Knowledge Diversion for Efficient Morphology Control and Policy Transfer
The Extra Tokens Matter: Disentangled Representation Learning with Vision Transformers
On the Role of Batch Size in Stochastic Conditional Gradient Methods
Navigating the Energy Landscape of Collaboration: Multi-Agent Communication Graph Generation via Score-Based Diffusion
Open-Text Aerial Detection: A Unified Framework For Aerial Visual Grounding And Detection
WildCat: Near-Linear Attention in Theory and Practice
Meerkat-VL: Implicit Risk Safety Alignment in Multimodal LLMs via Perceptual Reasoning and Self-Verification
VideoVeritas: AI-Generated Video Detection via Perception Pretext Reinforcement Learning
Neural Honeytrace: Plug&Play Watermarking Framework against Model Extraction Attacks
Conditional Diffusion Sampling
Distributionally Robust Set Representation Learning Under Inference-Time Element Corruption
Learning a Generative Meta-Model of LLM Activations
Tight Stability Bounds for Robust Distributed Learning: Byzantine Failures Hurt Generalization More than Data Poisoning
Online Learning with Recency: Algorithms for Sliding-window Streaming Multi-armed Bandits
Generative Representation Learning on Hyper-relational Knowledge Graphs via Masked Discrete Diffusion
On the Plasticity and Stability for Post-Training Large Language Models
Scaling Long-Horizon Agent via Context Folding
Improving the Sensitivity of Backdoor Detectors via Class Subspace Orthogonalization
Protein Autoregressive Modeling via Multiscale Structure Generation
Probabilistic Retrofitting of Learned Simulators
Set-Coupled Guidance: Set-Level Coordination in Diffusion-Based Dataset Distillation
Hierarchical Image Tokenization for Multi-Scale Image Super Resolution
Mind the Budget: Accelerating Deep Reinforcement Learning using Constrained Early Exit Neural Networks
Does AI Reviewer See the Full Picture? Attacking and Defending Multimodal Peer Review
Chasing Moving Targets with Online Self-Play Reinforcement Learning for Safer Language Models
Plug-and-Play Spiking Operators: Breaking the Nonlinearity Bottleneck in Spiking Transformers
Bottleneck-Guided Spectral Subgoals For Offline Goal-Conditioned RL
FIRE-Bench: Evaluating AI Agents on the Rediscovery of Scientific Insights
OGPO: Sample Efficient Full-Finetuning of Generative Control Policies
Use What You Know: Causal Foundation Models with Partial Graphs
Var-JEPA: A Variational Formulation of the Joint-Embedding Predictive Architecture – Bridging Predictive and Generative Self-Supervised Learning
Imitation Learning for Multi-turn LM Agents via On-policy Expert Corrections
When Softmax Fails at the Top: Extreme‑Value Corrections for InfoNCE
Robust Federated Learning Against Adaptive Compression
RL4RLA: Teaching ML to Discover Randomized Linear Algebra Algorithms Through Curriculum Design and Graph-Based Search
Guided Star-Shaped Masked Diffusion
UniDrag: Unified Multi-Field Prediction and Robust Shape Optimization for Vehicle Aerodynamics
Compositional Behavioral Semantics for State Abstraction in Reinforcement Learning
Physics-Informed Diffusion Models in Spectral Space
Neural QAOA$^2$: Differentiable Joint Graph Partitioning and Parameter Initialization for Quantum Combinatorial Optimization
ResRL: Boosting LLM Reasoning via Negative Sample Projection Residual Reinforcement Learning
Effective Distillation to Hybrid xLSTM Architectures
PLoRA: Efficient Concurrent LoRA Training for Large Language Models
Adversarial Attack and Defense for Denoising Diffusion Sampling
Proactive Defense Benchmark against Deepfake Generation
Quadratically Regularized Optimal Transport: Localization Bounds and Affine Case Analysis
SAGE-NAS: Synergizing LLM-Based Semantic Agent with Graph-Based Evaluator for Neural Architecture Search
NanoSpec: Accelerating Speculative Decoding using Minimalist In-Context Vocabularies
MEC: Machine-Learning-Assisted Generalized Entropy Calibration for Semi-Supervised Mean Estimation
UniSVQ: 2-bit Unified Scalar-Vector Quantization
MaxSAT-Based Compression for Tsetlin Machines
Navigating the Flatlands: Dual Adaptive Sharpness-Aware Minimization for Domain Generalization
Variational Entropic Optimal Transport
Understanding Generalization from Embedding Dimension and Distributional Convergence
FOAM: Blocked State Folding for Memory-Efficient LLM Training
Latent Guided Sampling for Combinatorial Optimization
GFMate: Empowering Graph Foundation Models with Test-time Prompt Tuning
KnapSpec: Self-Speculative Decoding via Adaptive Layer Selection as a Knapsack Problem
FedPissa: Towards Federated Personalized Adaptation of Foundation Models via LoRA Subspace Mapping
FedCDWA: Decoupled Federated Prototype Distillation with Hierarchical Wasserstein Aggregation
Privasis: Synthesizing the Largest "Public" Private Dataset from Scratch
Revisiting Positive Samples in Graph Contrastive Learning: From the Perspective of Message Passing
Enhancing Multi-Modal LLMs Reasoning via Difficulty-Aware Group Normalization
A Graph Foundation Model with Cross-Modal Alignment and Modality-Aware Expert Fusion for Multi-Modal Graphs
Video-SVD: Efficient Video Diffusion via Orthogonal Basis Composition
Probabilistic Salient Object Ranking
Unlearning Isn’t Forgetting: Revealing Hidden Leakage in Class Unlearning Evaluations
A Theory of How Pretraining Shapes Inductive Bias in Fine-Tuning
Safeguarded Stochastic Polyak Step Sizes for Non-smooth Optimization: Robust Performance Without Small (Sub)Gradients
Exposing Hidden Biases in Text-to-Image Models via Automated Prompt Search
GCIB: Graph Contrastive Information Bottleneck for Multi-Behavior Recommendation
Towards Generative Graph Matching for Graph Edit Distance Computation
DAG: A Dual Correlation Network for Time Series Forecasting with Exogenous Variables
Attention Sink Forges Native MoE in Attention Layers: Sink-Aware Training to Address Head Collapse
Fine-Tuning Without Forgetting In-Context Learning: A Theoretical Analysis of Linear Attention Models
Embedding Hybrid Systems into Continuous Latent Vector Fields
Creat3r: Confidence Reaggregation for Exploration-aware Active 3D Reconstruction
Trust-Region Diffusion Policies for Massively Parallel On-Policy RL
Reinforcement Learning with Action-Triggered Observations
Transformers Can Learn Posterior Predictive Distributions In-Context
LLM Self-Recognition: Steering and Retrieving Activation Signatures
Rethinking Calibration for Early-Exit Neural Networks
AnalogVerifier: A Neuro-Symbolic Framework for Analog Circuit Verification
Open-o3-Video: Grounded Video Reasoning with Explicit Spatio-Temporal Evidence
DiffThinker: Towards Generative Multimodal Reasoning with Diffusion Models
Best-of-Both-Worlds for Heavy-Tailed Markov Decision Processes
Scheduling Thoughts: Learning the Order of Thought in Diffusion Language Models
GeoMoLa: Geometry-Aware Motion Latents for Learning Robust Manipulation Policies
Towards Execution-Grounded Automated AI Research
SphericalDreamer: Generating Navigable Immersive 3D Worlds with Panorama Fusion
BYORn: Bootstrap Your Own Responses to Defend Large Vision-Language Models Against Backdoor Attacks
Reconstructing Template-Memorized Images from Natural Prompts
Is Spurious Correlation Removal Always Learnable?
Tempora: Characterising the Time-Contingent Utility of Online Test-Time Adaptation
Semi-Supervised Noise Adaptation: Transferring Knowledge from Noise Domain
BRIDGE: Triangular Fixed-Point Refinement for Long-Horizon Persona Consistency
Local Constrained Bayesian Optimization
Alterbute: Editing Intrinsic Attributes of Objects in Images
Doc-to-LoRA: Learning to Instantly Internalize Contexts
Stronger Benchmarks for Prediction as a Service with Constraints
Anytime Safe PAC Efficient Reasoning
Fine-Tune Once, Reuse Across Models: Bayesian Task-Update Factors and Approximations
Robust Signal Enhancement via Fractional Detail Views and Knowledge Guided Multi-view Fusion
Empty Shelves or Lost Keys? Recall Is the Bottleneck for Parametric Factuality
Fine-to-Coarse Fairness-Informed Multi-View Clustering
Universal Learning of Nonlinear Dynamics
Solving Spatial-Spectral Fusion with Latent Spectral Operators
Brep2Shape: Boundary and Shape Representation Alignment via Self-supervised Transformers
Active Learning with Low-Rank Structure for Data Selection
The Deterministic Horizon: When Extended Reasoning Fails and Tool Delegation Becomes Necessary
Generalizing Multi-Scale Time-Series Modeling with a Single Operator
Structure Enables Effective Self-Localization of Errors in LLMs
No Need to Train Your RDB Foundation Model
Towards One-to-Many Temporal Grounding
Budget-Feasible Mechanisms for Submodular Welfare Maximization in Procurement Auctions
The Optimal Token Baseline: Variance Reduction for Long-Horizon LLM-RL
CircuitPrint: Mechanistic Circuit Fingerprints for Large Language Models
DR$^2$Seg: Decomposed Two-Stage Rollouts for Efficient Reasoning Segmentation in Multimodal Large Language Models
T-GINEE: A Tensor-Based Multi-Graph Representation Learning
Capacity-Agnostic Parameter Isolation for Continual Graph Learning
Bulk-Calibrated Credal Ambiguity Sets: Fast, Tractable Decision Making under Out-of-Sample Contamination
Return of Frustratingly Easy Unsupervised Video Domain Adaptation
On Path to Multimodal Historical Reasoning: HistBench and HistAgent
AgentSteerTTS: A Multi-Agent Closed-Loop Framework for Composite-Instruction Text-to-Speech
Follow-the-Perturbed-Leader for Decoupled Bandits: Best-of-Both-Worlds and Practicality
OmniVideo-R1: Reinforcing Audio-visual Reasoning with Query Intention and Modality Attention
Axiomatic Atlas: A Prescriptive Framework for Neural Architecture Design
A Task-centric Theory for Iterative Self-Improvement with Easy-to-Hard Curricula
Scene Graph Thinking: Reinforcing Structured Visual Reasoning for Multimodal Large Language Models
Latent Representation Alignment for Offline Goal-Conditioned Reinforcement Learning
From Flat Facts to Sharp Hallucinations: Detecting Stubborn Errors via Gradient Sensitivity
RedVisor: Reasoning-Aware Prompt Injection Defense via Zero-Copy KV Cache Reuse
Supervised Guidance Training for Infinite-Dimensional Diffusion Models
Are First-Order Diffusion Samplers Really Slower? A Fast Forward-Value Approach
Hierarchical Representations for Cross-task Automated Heuristic Design using LLMs
Steer Where It Matters: Token-Level Visual-Sensitivity Steering for LVLMs Hallucination Mitigation
BOCLOAK: Optimal Transport-Guided Adversarial Attacks on Graph Neural Network-Based Bot Detection
PGD-NO: A Neural Operator with Precomputed Geometry Decomposition for 3D Million-Scale Physics Simulations
Zero-Flow Encoders
Hidden in Plain Tokens: Simply Robust, Gradient-Free Watermark for Synthetic Audio
Reasoning LLM Improves Speaker Recognition in Long-form TV Dramas
CRPO: Character-centric Group Relative Policy Optimization for Role-aware Reasoning in Role-playing Agents
Scalable Event Cloud Network for Event-based Classification
Lions and Muons: Optimization via Stochastic Frank-Wolfe under Heavy-Tailed Noise
Convergence Rate Analysis of the AdamW-Style Shampoo: Unifying One-Sided and Two-Sided Preconditioning
Intervene When It Doubts: Conjunction-Guided Interactive Reasoning
Deep Forcing: Training-Free Long Video Generation with Deep Sink and Participative Compression
ChaosNexus: A Foundation Model for ODE-based Chaotic System Forecasting with Hierarchical Multi-scale Awareness
Enhancing Protein-Protein Interaction Prediction with Hierarchical Motif-based Multimodal Protein Embedding
Differential Smoothing Mitigates Sharpening and Improves LLM Reasoning
Multi-Way Representation Alignment
Equivariant Latent Alignment via Flow Matching under Group Symmetries
Variational Learning of Disentangled Representations
CAMEL: Confidence-Gated Reflection for Reward Modeling
The Power of Power Law: Asymmetry Enables Compositional Reasoning
Hide and Seek in Embedding Space: Geometry-based Steganography and Detection in Large Language Models
Revisiting Efficiency–Accuracy Scaling in Mixture-of-Experts Architectures
Explainable Federated Learning via Global–Local Attribution Alignment
Finding Most Influential Sets
EvoMAS: Evolutionary Generation of Multi-Agent Systems
Show, Don't Tell: Morphing Latent Reasoning into Image Generation
SCOPE: Selective Conformal Optimized Pairwise LLM Judging
Stable Asynchrony: Variance-Controlled Off-Policy RL for LLMs
A Geometry-Based View of Mahalanobis OOD Detection
Weaving Graph over Tokens: Contextualizing Structured Sequences for LLMs
Interpretability Driven Evolutionary Approach for the Design of Biological Sequences
Reinforcement Learning for Reachability: Guaranteeing Asymptotic Optimality
Probing the Knowledge Boundary: An Interactive Agentic Framework for Deep Knowledge Extraction
Entangled No More: Multi-Domain Decoupling for Robust Dynamic Graph Neural Networks
Less Data, Faster Training: repeating smaller datasets speeds up learning via sampling biases
Is Code Better Than Language for Algorithmic Reasoning?
Factored Value Functions for Graph-Based Multi-Agent Reinforcement Learning
Don't Ignore the Tail: Decoupled Distillation Produces Top Maths Students on an Academic Budget
D$^3$: Dynamic Directional Graph-Constrained Data Scheduling for LLM Training
Towards One-for-All Anomaly Detection for Tabular Data
Expectation Consistency Loss: Rethink Confidence Calibration under Covariate Shift
Seeing to Generalize: How Visual Data Corrects Binding Shortcuts
TimeLAVA: Learning-Agnostic Valuation for Time Series Data
Attention Hijacking: Backdooring Text Dataset Distillation via Semantic Anchors
Spectral-Progressive Thought Flow for Lightweight Multimodal Reasoning
Narrowing the ANN–SNN Gap for Continuous 1D Temporal Signal Classification with Multi-Scale Temporal Encoding and Sparsity-Regularized Transform Encoding
LMCleaner: Efficient and Certified Online Unlearning via Influence Propagation Truncation
SubspacePath Pruner: Inference-time Pruning via Probe-based Representation–Parameter Coupling
Representational Curvature Modulates Behavioral Uncertainty in Large Language Models
TextResNet: Decoupling and Routing Optimization Signals in Compound AI Systems via Deep Residual Tuning
Squeezing More from the Stream : Learning Representation Online for Streaming Reinforcement Learning
RobuQ: Pushing DiTs to W1.58A2 via Robust Activation Quantization
Stabilizing In-Context Multi-Source Domain Adaptation for Biomedical Images Through Controls
AgentExpt: Automating AI Experiment Design with LLM-based Resource Retrieval Agent
Granularity-Aware Adaptive Classifier Expansion via Zero-Shot Learning
Transformers learn factored representations
Diffusion-based learning framework for Constrained Nonconvex Optimization with Weighted Bootstrapped Refinement
DLLMQuant: A Post-Training Quantization Framework Tailored for Diffusion-Based Large Language Models
Factor-Wise Homogeneity of Slot-Attention for Continual Object-Centric Learning
Reinforcement Learning with Discrete Diffusion Policies for Combinatorial Action Spaces
Can Adaptive Gradient Methods Converge under Heavy-Tailed Noise? A Case Study of AdaGrad
Stationary MMD Points
Decomposition-Based Modular Conformal Prediction for Two-Stage Modeling
Helpful to a Fault: Measuring Illicit Assistance in Multi-Turn, Multilingual LLM Agents
Learning to Rank by Directly Optimizing Full-Order Probabilities
GraphFLEx: Unsupervised Structure Learning $\underline{\text{F}}$ramework for $\underline{\text{L}}$arge $\underline{\text{Ex}}$panding $\underline{\text{Graph}}$s
Explanations are a Means to an End: Decision Theoretic Explanation Evaluation
PACE: Parameter Change for Unsupervised Environment Design
KAGE-Bench: Fast Known-Axis Visual Generalization Evaluation for Reinforcement Learning
RADAR: Defending RAG Dynamically against Retrieval Corruption
Streaming Sliced Optimal Transport
Order Matters: Unveiling the Hidden Impact of Macro Placement Sequences via Proxy-Guided LLM Evolution
Entropy-informed Decoding: Adaptive Information-Driven Branching
Which Heads Matter for Reasoning? RL-Guided KV Cache Compression
MTNL: A Unified Modeling Perspective for Enhancing Tensor Network Learning
Evaluating Newtonian Mechanics in Video Generative Models with Real Physical Systems
Rel-MOSS: Towards Imbalanced Relational Deep Learning on Relational Databases
Privacy-Aware Data Integration for Enhanced Quantile Inference under Heterogeneity
SCRWKV: Ultra-Compact Structure-Calibrated Vision-RWKV for Topological Crack Segmentation
FedSDR: Federated Self-Distillation with Rectification
Breaking the Factorization Barrier in Diffusion Language Models
Knapsack RL: Compute-Efficient Reinforcement Learning via Heterogeneous Rollout Allocation
RealisMotion: Decomposed Human Motion Control and Video Generation in the World Space
Sobolev Regularized Score Difference Estimation in Diffusion Models
Direct 3D-Aware Object Insertion via Decomposed Visual Proxies
Prototype-Based Test-Time Adaptation of Vision-Language Models
Last-Iterate Convergence of Regularized Gradient Methods for Stochastic Monotone Variational Inequalities
The Appeal and Reality of Recycling LoRAs with Adaptive Merging
Privileged Information Distillation for Language Models
Scalable RF Simulation in Generative 4D Worlds
SEPS: Semantic-Enhanced Patch Slimming Framework for Fine-Grained Cross-Modal Alignment
Localized, High-resolution Geographic Representations with Slepian Functions
Incremental Learning of Sparse Attention Patterns in Transformers
Decoupled Low-Rank Adaptation for Robust Federated Fine-Tuning
CB-SLICE: Concept-Based Interpretable Error Slice Discovery
Corrigibility Transformation: Constructing Goals That Accept Updates
Weight Updates as Activation Shifts: A Principled Framework for Steering
ConServe: Fine-Grained GPU Harvesting for LLM Online and Offline Co-Serving
Fast Mixture of Curvature-Aware Experts for Diverse and Dynamic Graph Topologies
Federated Multi-view Clustering for Remote Sensing Data
Policy-Driven World Model Adaptation for Robust Offline Model-based Reinforcement Learning
Cardio-mmFlow: A Gaussian-Prior-Free Physics-Informed Flow Matching Framework for Electrocardiogram to mmWave Radar Synthesis
Proxy Compression for Language Modeling
LECTOR: Joint Learning of Scientific Reasoning Graphs and Introduction Generation
A Tight Theory of Error Feedback Algorithms in Distributed Optimization
Backward Oversmoothing: why is it hard to train deep Graph Neural Networks?
Conditional Equivalence of DPO and RLHF: Assumptions, Failure Modes, and Provable Alignment
Self-Guidance: Enhancing Neural Codecs via Decoder Manifold Alignment
Restoring Initial Noise Sensitivity in Text-to-Image Distillation through Geometric Alignment
Data Reconstruction: Identifiability and Optimization with Sample Splitting
SynGR: Unleashing the Potential of Cross-Modal Synergy for Generative Recommendation
Richer Bayesian Last Layers with Subsampled NTK Features
Towards Universal Gene Regulatory Network Inference: Unlocking Generalizable Regulatory Knowledge in Single-cell Foundation Models
Scaling by Diversified Experience for Vision-Language-Action Models
On Group Relative Policy Optimization Collapse in Agent Search: The Lazy Likelihood-Displacement
Well-Posed KL-Regularized Control via Wasserstein and Kalman–Wasserstein KL Divergences
When Simple Problems Wear Complex Costumes: Improving Efficiency in LRM's Adaptive Reasoning
Non-Parametric Probabilistic Robustness: A Conservative Risk Estimator under Unknown Perturbation Distributions
The Velocity Deficit: Initial Energy Injection for Flow Matching
Dreaming in Code for Curriculum Learning in Open-Ended Worlds
AlphaGRPO: Unlocking Self-Reflective Multimodal Generation in Unified Multimodal Models via Decompositional Verifiable Reward
On the existence of consistent adversarial attacks in high-dimensional linear classification
Tokenised Flow Matching for Hierarchical Simulation Based Inference
Trajectory Stitching for Solving Inverse Problems with Flow-Based Models
Towards Completeness in Causal Discovery from Soft Interventions with Known Targets
Predictive variational inference: Learn the predictively optimal posterior distribution
Ubiquity of Emergent Hebbian Dynamics in Regularized Learning
Threshold-Based Exclusive Batching for LLM Inference
Tracking Drift: Variation-Aware Entropy Scheduling for Non-Stationary Reinforcement Learning
MixFP4: Enhancing NVFP4 with Adaptive FP4/INT4 Block Representations
Towards Understanding the Dynamics of Low-Rank Adaptation
Trust Region Masking for Long-Horizon LLM Reinforcement Learning
Asymmetric conformal prediction with penalized kernel sum-of-squares
Rethinking Convergence in MoE Training: The Role of Routing Sparsity
DSGCR: Decomposed Spectral Geometry-Aware Cross-Modal Semantic Representation for 3D Visual Grounding
SimulCost: A Cost-Aware Benchmark and Toolkit for Automating Physics Simulations with LLMs
Dynamics and Representation Structure of Local Approximations to Gradient-Based Learning in Linear Recurrent Neural Networks
ANTiC: Adaptive Neural Temporal In Situ Compressor
Proteo-R1: Reasoning Foundation Models for De Novo Protein Design
Variational Learning for Insertion-based Generation
The Structural Origin of Attention Sink: Variance Discrepancy, Super Neurons, and Dimension Disparity
URS: A Unified Neural Routing Solver for Cross-Problem Zero-Shot Generalization
Contrastive Flow Map Matching
Topological Active Inference for Task Disambiguation
ReCoG: Relational and Compact Context Graph Learning for Few-shot Molecular Property Prediction
STLA: Spatiotemporal Lookahead Alignment for Post-Training Quantization
ParisKV: Fast and Drift-Robust KV-Cache Retrieval for Long-Context LLMs
Adaptive Symmetry Discovery for Dynamical System Identification
CANDI: Hybrid Discrete-Continuous Diffusion Models
Relative Entropy Estimation in Function Space: Theory and Applications to Trajectory Inference
FAB: A First-Order AB-based Gradient Algorithm for Distributed Bilevel Optimization over Time-Varying Directed Graphs
Leak@$k$: Unlearning Does Not Make LLMs Forget Under Probabilistic Decoding
ElicitR: Unlocking Latent Reasoning in Dense Retrievers via Generative Regularization
On the Learnability of Test-Time Adaptation: A Recovery Complexity Perspective
Semantic-Aware Motion Encoding for Topology-Agnostic Character Animation
Uncovering Latent Communication Patterns in Brain Networks via Adaptive Flow Routing
Secure Multi-agent Reinforcement Learning for Service Systems with Affinity and Byzantine Nodes: Stability Analysis and Protection Design
EvoMAS: Heuristics in the Loop—Evolving Smarter Agentic Workflows
SCoA: Revisiting Domain Generalized Object Detection with Style-Conditioned Adaptation
Expand Neurons, Not Parameters
Measuring and Mitigating Post-Hoc Rationalization in Reverse Chain-of-Thought Generation
scCBGM: Single-Cell Editing via Concept Bottlenecks
Bilinear Bandits with Partially Observable Features
Echoes within the Reasoning: Stealthy and Effective Watermarking via Chain of Thought
Fast Mixing Steady-State Control in Markov Decision Processes
COGNOS: Universal Enhancement for Time Series Anomaly Detection via Constrained Gaussian-Noise Optimization and Smoothing
Self-Supervised Dynamical System Representations for Physiological Time-Series
Black-Box Assisted Regression: Phase Transitions and Minimax Optimality
Efficient Training of Boltzmann Generators Using Off-Policy Log-Dispersion Regularization
Remove the Ambiguity: Few-shot Multimodal Anomaly Detection Using Crossmodal Feature Replacers
Dynamic Regret via Discounted-to-Dynamic Reduction with Applications to Curved Losses and Adam Optimizer
Interpretable Discovery of One-parameter Subgroups: A Modular Framework for Elliptical, Hyperbolic, and Parabolic Symmetries
HOI-PAGE: Zero-Shot Human-Object Interaction Generation with Part Affordance Guidance
InfoDLM: an Information-Adaptive Framework for Discrete Diffusion Language Model Pretraining
QuArch: A Benchmark for Evaluating LLM Reasoning in Computer Architecture
LayerT2V: A Unified Multi-Layer Video Generation Framework
Branch Scaling Manifests as Implicit Architectural Regularization for Improving Generalization in Overparameterized ResNets
Learn to Merge: Meta-Learning for Adaptive Multi-Task Model Merging
From Noise to Intent: Anchoring Generative VLA Policies with Residual Bridges
MonoScale: Scaling Multi-Agent System with Monotonic Improvement
Learning Partial Concept Classes and Universal Rates Under Massart Noise
DuetServe: Harmonizing Prefill and Decode for LLM Serving via Adaptive GPU Multiplexing
Dissecting Causal Mechanism Shifts via FANS: Function And Noise Separation
Cross-task Calibration for Asynchronous Federated Continual Learning
DenseSteer: Steering Small Language Models towards Dense Math Reasoning
IMPACT: Influence Modeling for Open-Set Time Series Anomaly Detection
SWE-ABS: Adversarial Benchmark Strengthening Exposes Inflated Success Rates on Test-based Benchmark
BeaconKV: Key-Value Cache Compression Guided by Beacon Queries for Efficient Large Reasoning Model Inference
Black-Box Combinatorial Optimization with Order-Invariant Reinforcement Learning
Learning Human-Robot Collaboration via Heterogeneous-Agent Lyapunov Policy Optimization
Zooming without Zooming: Region-to-Image Distillation for Fine-Grained Multimodal Perception
Joint Geometric and Trajectory Consistency Learning for One-Step Real-World Super-Resolution
IDLM: Inverse-distilled Diffusion Language Models
Learning a Zeroth-Order Optimizer for Fine-Tuning LLMs
Semantic Editing with Coupled Stochastic Differential Equations
Two-Layer Linear Auto-Regressive Models Estimate Latent States
Agentic Proposing: Enhancing Large language Model Reasoning via Compositional Skill Synthesis
LiveFigure: Generating Editable Scientific Illustration with VLM Agents
RAT+: Train Dense, Infer Sparse - Recurrence Augmented Attention for Dilated Inference
Faults in Our Formal Benchmarking: Dataset Defects and Evaluation Failures in Lean Theorem Proving
Are We Overconfident in Models and Results for Semi-Supervised 3D Medical Image Segmentation?
TetraJet-v2: Accurate NVFP4 Training for Large Language Models with Oscillation Suppression and Outlier Control
Decoupling Variance and Scale-Invariant Updates in Adaptive Gradient Descent for Unified Vector and Matrix Optimization
FedVeer: Self-Adaptive Skew Estimation for Robust Federated Learning
A Fully First-Order Layer for Differentiable Optimization
On Stable Long-Form Generation: Benchmarking and Mitigating Length Volatility
Beyond Confidence: Adaptive and Coherent Decoding for Diffusion Language Models
Test-Time Debiasing with Probabilistic Prompts via Wasserstein Distance in Vision-Language Models
Benchmarking the Scientific Mind: A Pathology-Derived Biomedical VQA Benchmark for Complex Scientific Reasoning
The Safety-Aware Denoiser for Text Diffusion Models
ThetaEvolve: Test-time Learning on Open Problems
Crisp: A Spectral-Based Interaction Strategy for Multivariate Time Series Forecasting
PLANTAIN: Plan-Answer Interleaved Reasoning
AsyncSpade: Efficient Test-Time Scaling with Asynchronous Sparse Decoding
LEC: Linear Expectation Constraints for Selection-Conditioned Risk Control in Selective Prediction and Routing Systems
When Drafts Evolve: Speculative Decoding Meets Online Learning
Collapsed Effective Operators for Higher-order Structures
EMBGuard: Constructing Hazard-Aware Guardrails for Safe Planning in Embodied Agents
SALSA-V: Shortcut-Augmented Long-form Synchronized Audio from Videos
Unifying Heterogeneous Degradations: Uncertainty-Aware Diffusion Bridge Model for All-in-One Image Restoration
DSENet: A Novel Dual-Stream Enhancement Network for Multi-Scale Non-Stationary Time Series Forecasting
Watch Your Step: Information Injection in Diffusion Models via Shadow Timestep Embedding
RGGT: A Generative-Prior-Guided Transformer for Unified Rigid and Non-Rigid Point Cloud Registration
Improving the Robustness-Utility Trade-off in Decentralized Learning over Sparse Networks
Instance-Dependent Continuous-Time Reinforcement Learning via Maximum Likelihood Estimation
Merge to Remember: Sharpness-Aware Isotropic Merging for Continual Learning
MultiLoReFT: Decoupling Shared and Modality-Specific Subspaces in Multimodal Learning via Low-Rank Representation Fine-Tuning
Beyond Euclidean Summaries: Online Change Point Detection for Distribution-Valued Data
AlignedNorm: Prompting Vision–Language Models via Coupled Prompt Field
DistFlow: A Fully Distributed RL Framework for Scalable and Efficient LLM Post-Training
Affine-Scaled Attention: Towards Flexible and Stable Transformer Attention
TokenRatio: Principled Token-Level Preference Optimization via Ratio Matching
On the Power of Statistics in Class-Incremental Learning with Pretrained Models
Overthinking: Amplifying Reasoning Weights to Extract Learned Secrets
GP2F: Cross-Domain Graph Prompting with Adaptive Fusion of Pre-trained Graph Neural Networks
Neural Quantum States in Mixed Precision
Scaling Behavior in Model Fine-tuning for Audio DeepFake Detection
Efficiently Training Time-to-First-Spike Spiking Neural Networks from Scratch
CaliDist: Calibrating Large Language Models via Behavioral Robustness to Distraction
Learn-to-learn on Arbitrary Textual Conditioning: A Hypernetwork-Driven Meta-gated LLM
Reuse your FLOPs: Scaling RL on Hard Problems by Conditioning on Very Off-Policy Prefixes
Online Linear Programming for Multi-Objective Routing in LLM Serving
Towards Efficient LLMs Annealing with Principled Sample Selection
Selecting Samples on Graphs: A Unified Dataset Pruning Framework for Lossless Training Acceleration
On the Theory of Continual Learning with Gradient Descent for Neural Networks
Edit-Based Refinement for Parallel Masked Diffusion Language Models
Learning Tight Rejection Boundaries without Negatives for Strict One-Class Audio Deepfake Detection
Learning Generalized Trackers with Elastic Token Budgets
AD-BTS: Adaptive Dual-Branch Token Sparsification via Spatial Information Density
Cold-Start Personalization via Bayesian Adaptive Questioning
Long Grounded Thoughts: Synthesizing Visual Problems and Reasoning Chains at Scale
Evaluating Contextual Illegality: AI Compliance in Corporate Law Scenarios
Deep Learning for BioImaging: What Are We Really Learning?
Immuno-VLM: Immunizing Large Vision-Language Models via Generative Semantic Antibodies for Open-World Trustworthiness
Transitive Representation Learning Enhances Histopathology Annotation
Density-Aware Translation of Spurious Correlations in Zero-Shot VLMs
Posterior Concentration of Bayesian Physics-Informed Neural Networks for Elliptic PDEs
EvoC2F: Compiling Tool Orchestration for Efficient and Evolvable LLM Agents
How Good is Post-Hoc Watermarking With Language Model Rephrasing?
Stabilizing MoE Reinforcement Learning by Aligning Training and Inference Routers
SHINE: A Scalable In-Context Hypernetwork for Mapping Context to LoRA in a Single Pass
Deep Neural Network Regression with Functional Covariates
Multimodal Latent Language Modeling with Next-Token Diffusion
Diffusion Models Preferentially Memorize Prototypical Examples or: Why Does My Diffusion Model Love Slop?
Likelihood over Estimation: Robust Quadratic Discriminant Analysis for Heavy-Tailed Distributions with Theory and Evidence
Bend the Basics: Degradation-Aware Deformable Tokenization for All-in-One Image Restoration
TFTF: Training-Free Targeted Flow for Conditional Sampling
BabyVision: Visual Reasoning Beyond Language
Winformer: Transcending Pairwise Similarity for Time-series Generation
RAG without Forgetting: Continual Query-Infused Key Memory
DF-LoGiT: Data-Free Logic-Gated Backdoor Attacks in Vision Transformers
Deep Networks Learn Deep Hierarchical Models
FUSE: FK-Steered Multi-Modal Flow Matching for Efficient Simulation-Based Posterior Estimation
Stochastic Neural Ray Tracing for Radio Frequency Channel Modeling
Towards Practical World Model-based Reinforcement Learning for Vision-Language-Action Models
Speedup Patch: Learning a Plug-and-Play Policy to Accelerate Embodied Manipulation
DriveWorld-VLA: Unified Latent-Space World Modeling with Vision–Language–Action for Autonomous Driving
SimGFM: Simplifying Discrete Flow Matching for Graph Generation
Breaking the Synthetic-Real Domain Shortcut for Training-Free Generative Replay-based Class Incremental Learning
Learning the Best Under Constraints: A Duality-Based Framework
TarGATE: Target-Aware Data Selection via Token-Attenuation Gates
How Should Transformers Encode Numeric Values in Electronic Health Records?
Online Continual Learning with Dynamic Label Hierarchies
Asking What Matters: Reward-Driven Clarification for Software Engineering Tasks
Stabilizing Reinforcement Learning for Diffusion Language Models
SwitchCraft: A Programmatic Framework for Designing State-Switching Proteins
Learning Attribute–Affordance Hierarchies in Hyperbolic Space for Open-Vocabulary 3D Object Affordance Grounding
OSCS: Online Selection with Provable FAR Control for LLM Safety
Can LLMs Reason Like Automated Theorem Provers for Rust Verification? VCoT-Bench: Evaluating via Verification Chain of Thought
LaRI: Layered Ray Intersections for Single-view 3D Geometric Reasoning
$f$-Divergence Self-Play for Tabular Anomaly Detection via Large Language Models
The Accumulation of Score Estimation Error in Diffusion Models
How Does Reasoning Flow? Tracing Attention-Induced Information Flow for Targeted RL in LLMs
Block-wise Codeword Embedding for Reliable Multi-bit Text Watermarking
Long-term Fairness with Selective Labels
Decompose and Recompose: Reasoning New Skills from Existing Abilities for Cross-Task Robotic Manipulation
Dual Latent Memory for Visual Multi-agent System
ReAugment: Targeted Few-Shot Time Series Augmentation via Model Zoo-Guided Reinforcement Learning
DocVAL: Validated Chain-of-Thought Distillation for Grounded Document VQA
Coupled Variational Reinforcement Learning for Language Model General Reasoning
Dynamic Decision Learning: Test-Time Evolution for Abnormality Grounding in Rare Diseases
Evaluating and Rewarding LALMs for Expressive Role-Play TTS via Mean Continuation Log-Probability
Sparser, Faster, Lighter Transformer Language Models
Agent-Omit: Adaptive Context Omission for Efficient LLM Agents
LithoDreamer: A Physics-Informed World Model for Multi-Stage Computational Lithography
VPD-100K: Towards Generalizable and Fine-grained Visual Privacy Protection
Improving CLIP Adaptation by Breaking Tail Alignment for Source-Free Cross-Domain Few-Shot Learning
Multi-marginal temporal Schrödinger Bridge Matching from unpaired data
PromptRL: Prompt Matters in RL for Flow-Based Image Generation
DiFA: Inference-Time Forward-Process Alignment for Diffusion Models
Peer-Preservation in Frontier Models
Outrunning LLM Cutoffs: A Live Kernel Crash Resolution Benchmark for All
TUR-DPO: Topology- and Uncertainty-Aware Direct Preference Optimization
CoGe-GCD: Reframing Generalized Category Discovery with Compositional Generalization
When Can We Trust Survival Model Evaluation ?
Unifying Deep Stochastic Processes for Image Enhancement
Dual Optimal Transport for Multi-Concept Composition: Structural Alignment and Texture Injection in Diffusion Models
T-POP: Test-Time Personalization with Online Preference Feedback
IVQ: Structured and Lightweight Vector Quantization via Binary Hierarchical Composition Inspired by $\textit{IChing}$
NAACA: Training-Free NeuroAuditory Attentive Cognitive Architecture with Oscillatory Working Memory for Salience-Driven Attention Gating
Rethinking Evaluation Paradigms in IBP-based Certified Training
Box Thirding: Anytime Best Arm Identification under Insufficient Sampling
Efficient Adaptive Testing via Gradient Path Matching Subset Selection for AI Education
Multi-Agent Teams Hold Experts Back
CUARewardBench: A Benchmark for Evaluating Reward Models for Computer-Using Agents
Functional building blocks of neural networks: from network motifs to collective dynamics
M+Adam: Low-Precision Training via Additive–Multiplicative Optimization
CorrectionPlanner: Self-Correction Planner with Reinforcement Learning in Autonomous Driving
In-Context Generation with Regional Constraints for Instructional Video Editing
Unsupervised Camouflaged Object Detection with Dual-Eigenvector Spectral Pseudo-Labeling and Contrastive Refinement
Near-Optimal Regret for KL-Regularized Multi-Armed Bandits
Towards Professional-Grade Financial Agents: Benchmarking, Tooling, and Structured Reasoning
PRAC: Principal-Random Subspace for LLM Activation Compression and Memory-Efficient Training
Local Redundancy: An Information-Theoretic Measure of Plasticity from Synthetic Memorization
DLO-Lab: Benchmarking Deformable Linear Object Manipulations with Differentiable Physics
DyCon: Dynamic Reasoning Control via Evolving Difficulty Modeling
Non-Parametric Structural Priors for Geometry Theorem Prediction
SINQ: Sinkhorn-Normalized Quantization for Calibration-Free Low-Precision LLM Weights
Faithful Mobile GUI Agents with Guided Advantage Estimator
History-Bootstrapped Flow Matching for Inverse Boiling Reconstruction
Risk-Bounded Distribution Reconstruction: Stable Statistic Calibration for Long-Tailed Recognition
$\tau$-Knowledge: Evaluating Conversational Agents over Unstructured Knowledge
Pluralistic Leaderboards
Variational Flow Maps: Make Some Noise for One-Step Conditional Generation
Adversarial Dual On-Policy Distillation from Expressive Teacher
Estimation of Treatment Effects Under Nonstationarity via the Truncated Policy Gradient Estimator
SL-VC: A Benchmark and Automated Framework for Separation Logic Verification Condition Proving
Midtraining Bridges Pretraining and Posttraining Distributions
TF-FACE: Time-Frequency Fusion Learning via Frequency-Domain Adaptive and Controllable Enhancement for Trajectory Prediction
Hierarchical Multi Scale Graph Neural Networks: Scalable Heterophilous Learning with Oversmoothing and Oversquashing Mitigation
CoCoEdit: Content-Consistent Image Editing via Region Regularized Reinforcement Learning
Optimizing Visual Generative Models via Distribution-wise Rewards
Beyond Extrapolation: Knowledge Utilization Paradigm with Bidirectional Inspiration for Time Series Forecasting
Hybrid-Gym: Training Coding Agents to Generalize Across Tasks
PolySAE: Modeling Feature Interactions in Sparse Autoencoders via Polynomial Decoding
Bridging Spherical Black-Box Optimizers
Topology-Aware Contrastive Learning: Regulating Representation Connectivity via Persistent Homology
Regret-Based Federated Causal Discovery with Unknown Interventions
AvAtar: Learning to Align via Active Optimal Transport
E-mem: Multi-Agent Based Episodic Context Reconstruction for LLM Agent Memory
EntroKV: Entropy-Guided Dynamic Budget Allocation for KV-Cache Compression
Self-Supervised Weight Templates for Scalable Vision Model Initialization
SAMT: Generating Structured Avatar Meshes and Textures from a Single Image
InfiMed-ORBIT: Aligning LLMs on Open-Ended Complex Tasks via Rubric-Based Incremental Training
Quantum Algorithms for Triangle Cut Sparsification
SALE : Low-bit Estimation for Efficient Sparse Attention in Long-context LLM Prefilling
Generalization and Scaling Laws for Mixture-of-ExpertsTransformers
Reparameterization Flow Policy Optimization
ImmersePro: End-to-End Stereo Video Synthesis Via Implicit Disparity Learning
FiX: Introducing Fine-grained Forget Gate into Softmax Attention
RBCBF: Decoding Time Safety Alignment via Risk Guided Rollback and Barrier Control
CSPLoRA: Confidence-Guided Structure Planning for Low-Rank Adaptation
Unifying and Optimizing Data Values for Selection via Sequential Decision-Making
HypRAG: Hyperbolic Dense Retrieval for Retrieval Augmented Generation
Component-Wise Composite Likelihood Distillation for Censored Time-to-Event Data
Temporal Score Rescaling for Temperature Sampling in Diffusion and Flow Models
Unlocking Noise-Resistant Vision: Key Architectural Secrets for Robust Models Against Gaussian Noise
MMKU-Bench: A Multimodal Update Benchmark for Diverse Visual Knowledge
Deep Ensemble Clustering for Visual Representation Learning
Finding the Correct Visual Evidence Without Forgetting: Mitigating Hallucination in LVLMs via Inter-Layer Visual Attention Discrepancy
Relational Structural Causal Models
MultiBreak: A Scalable and Diverse Multi-turn Jailbreak Benchmark for Evaluating LLM Safety
Prediction-Powered Adaptive Inference with Pretrained AI Models for Contextual Bandits
Hearing Without Noticing? Attention-Aware Stealthy Black-Box Adversarial Audio Attacks
IBMA: Information Bottleneck-Based Multimodal Alignment
MetaMoE: Diversity-Aware Proxy Selection for Privacy-Preserving Mixture-of-Experts Unification
LightWM: Training-Free Hierarchical Working Memory for Small Language Model Agents
WorldTravel: A Realistic Multimodal Travel-Planning Benchmark with Tightly Coupled Constraints
Trajectory-Aware Heuristic Learning for Combinatorial Search
From Player to Master: Enhancing Test-Time Learning of LLM Agents via Reinforcement Learning over Memory
ArborKV: Structure-Aware KV Cache Management for Scaling Tree-based LLM Reasoning
Path-Decoupled Hyperbolic Flow Matching for Few-Shot Adaptation
Large Language Models Explore by Latent Distilling
MVR-cache: Optimizing Semantic Caching via Multi-Vector Retrieval and Learned Prompt Segmentation
Mitigating the Safety–Utility Trade-off in LLM Alignment via Adaptive Safe Context Learning
Implicit Actor Critic Coupling via a Supervised Learning Framework for RLVR
Responsible Text-to-Image Diffusion: Interpretable and Linearly Controllable Semantics for Fair and Safe Generation
Latent Space Robust Optimization of Neural Processes with Aligned Stratified Order-Statistic Loss Reduction
AnyEdit++: Adaptive Long-Form Knowledge Editing via Bayesian Surprise
Temporal Preference Optimization for Unsupervised Retrieval
Steady-State Behavior of Constant-Stepsize Stochastic Approximation: Gaussian Approximation and Tail Bounds
Lookahead Path Likelihood Optimization for Diffusion LLMs
Learning from Comparison: Constrained Projection Policy Optimization for Pareto-Front Improvement
Outcome Rewards Do Not Guarantee Verifiable or Causally Important Reasoning
LEAP: Zone-Aware MCTS for LLM Self-Speculative Decoding
Decoupled Training with Local Reinforcement Fine-Tuning in Federated Learning
Time Series Forecasting Through the Lens of Dynamics
GUI-Spotlight: Adaptive Iterative Focus Refinement for Enhanced GUI Visual Grounding
FrameOracle: Learning What to See and How Much to See in Videos
Mitigating Visual Hallucinations via Semantic Curriculum Preference Optimization in MLLMs
When Replanning Becomes the Bottleneck: Budgeted Replanning for Embodied Agents
Deriving Neural Scaling Laws from the Statistics of Natural Language
Beyond Blind Noising: Disentangled Visual Rectification for Hallucination Mitigation in MLLMs
ReSpinQuant: Efficient Layer-Wise LLM Quantization via Subspace Residual Rotation Approximation
Neural Modular Physics for Elastic Simulation
LieWarper: Geometry-Aware Motion Transfer via Lie Algebra
EEG-Based Multimodal Learning via Hyperbolic Mixture-of-Curvature Experts
Brain Networks Should Be Learned, Not Constructed
Mode Seeking meets Mean Seeking for Fast Long Video Generation
ADEPT: RL-Aligned Agentic Decoding of Emotion via Evidence Probing Tools — From Consensus Learning to Ambiguity-Driven Emotion Reasoning
Detecting Errors in AI-Generated Annotations: When and Why Semantic Neighbors Help
Anti-causal domain generalization: Leveraging unlabeled data
MOES-Pred: Molecular Structural Representation Learning by Adaptive Energy-Sentinel Vibration for Generalized Property Prediction
Preference-Enhanced Reinforcement Learning for Pluralistic Image Inpainting
SwiftPFN: Revisiting Row-Wise Attention–Only Tabular Foundation Models with Adaptive Early Exit
Deep Learning of Compositional Targets with Hierarchical Spectral Methods
Neural Collapse by Design: Learning Class Prototypes on the Hypersphere
Antidistillation Fingerprinting
Flash-GRPO: Efficient Alignment for Video Diffusion via One-Step Policy Optimization
SuCo: Sufficiency-guided Continuous Adaptive Reasoning
Finding Stationary Points by Comparisons
Towards Seed-Robust Safety Alignment in Text-to-Image Models
Muon in Associative Memory Learning: Training Dynamics and Scaling Laws
Noisy Pairwise-Comparison Random Search for Smooth Nonconvex Optimization
Trajectory-Stabilized Inference for Diffusion-Based Video Inpainting
Practical and Optimal Algorithm for Linear Contextual Bandits with Rare Parameter Updates
SSR-Merge: Subspace Signal Routing for Training-Free LoRA Merging in Diffusion Models
ManifoldKV: Training-Free KV Cache Compression via Euclidean Outlier Detection
Causal Direct Preference Optimization for Distributionally Robust Generative Recommendation
Forensic Prompting with Dual-Action Policy Optimization for Vision-Language Forgery Detection and Localization
When LLMs Develop Languages: Symbolic Communication for Efficient Multi-Agent Reasoning
Dependence-Aware Label Aggregation for LLM-as-a-Judge via Ising Models
Large Language Models as Topological Thinkers: A Benchmark on Graph Persistent Homology
Contextual Rollout Bandits for Reinforcement Learning with Verifiable Rewards
Demystifying Entropy Control in LLM RL Training: Theoretical Analysis and Dynamic Scheduling
Size Transferability of Graph Convolutional Networks across Sparsity: A Generalized Graphon Perspective
Value-as-Return: A Two-Stage Framework to Align on the Optimal Score Function
Physics-informed Neural Operator Learning for Nonlinear Grad-Shafranov Equation
Selling Data as a Digital Good with Scaling Valuations
Closing the Expression Gap in LLM Instructions via Socratic Questioning
FAST-AR: Fast Autoregressive Video Diffusion and World Models with Temporal Cache Compression and Sparse Attention
Tuning the Implicit Regularizer of Masked Diffusion Language Models: Enhancing Generalization via Insights from $k$-Parity
ProtoKV: Streaming Video Understanding under Delayed Query with Summary-State Memory
Infinite Mask Diffusion for Few-Step Distillation
MAS-ProVe: Understanding the Process Verification of Multi-Agent Systems
MIMOMamba: From Scalar Duality to Matrix-Valued Attention
Zeroth-Order Non-Log-Concave Sampling with Variance Reduction and Applications to Inverse Problems
LatentChem: From Textual CoT to Latent Thinking in Chemical Reasoning
StarEmbed: Benchmarking Time Series Foundation Models on Astronomical Observations of Variable Stars
The (Marginal) Value of a Search Ad: An Online Causal Framework for Repeated Second-price Auctions
BPL: Generalizable Deepfake Detection via Bias-only Pair-aware Learning
MedCoG: Maximizing LLM Inference Density in Medical Reasoning via Meta-Cognitive Regulation
Low Kruskal-Rank Adaptation
Boundary Embedding Shaping with Adaptive Contrastive Learning for Graph Structural Disentanglement
Domain-Shift-Aware Conformal Prediction for Large Language Models
Efficient Multi-modal Dataset Distillation via Analytic Parameter Matching
FakeWorld 1.0: An Omni-modal Benchmark for Fake Media and Content
A Game-Theoretic Framework for Measuring and Explaining Metric Compatibility in Fair Machine Learning
Global Convergence of Adaptive Sensing for Principal Eigenvector Estimation
Learning Dynamics of Zeroth-Order Optimization: A Kernel Perspective
SoMA: A Real-to-Sim Neural Simulator for Robotic Soft-Body Manipulation
Large-Scale Terminal Agentic Trajectory Generation from Dockerized Environments
Theoretical Perspectives on Data Quality and Synergistic Effects in Pre- and Post-Training Reasoning Models
Constrained hybrid modelling to predict microbial dynamics and organic matter turnover in soil systems
ImgCoT: Compressing Long Chain of Thought into Compact Visual Tokens for Efficient Reasoning of Large Language Model
Server-Proximal Aggregation for Federated Domain-Incremental Learning under Partial Participation: Task-Uniform Convergence and Backward Transfer
Characterization of Gaussian Universality Breakdown in High-Dimensional Empirical Risk Minimization
Focusing: View-Consistent Sparse Voxels for Efficient 3D VAE Training
VeRO: A Harness for Agents to Optimize Agents
Beyond Heuristic Tuning: Power-Calibrated LLM Watermarking
Training Deep Spiking Neural Networks without Normalization
CauScale: Neural Causal Discovery at Scale
Lightweight and Interpretable Transformer via Unrolling of Mixed Graph Algorithms for Traffic Forecast
De-Linearizing Agent Traces: Bayesian Inference of Latent Partial Orders for Efficient Execution
MemoryBench: A Benchmark for Memory and Continual Learning in LLM Systems
$\texttt{ShaplEIG}$: Bayesian Experimental Design for Shapley Value Estimation
XDomainBench: Diagnosing Reasoning Collapse in High-Dimensional Scientific Knowledge Composition
MoVie: Multimodal Video Compression with Text Guidance
OmniVL-Guard: Towards Unified Vision-Language Forgery Detection and Grounding via Balanced RL
GRASP: Awakening Latent Spatial Reasoning in LVLMs via Training-free Geometric Rectification
The Geometry of Narrow Fine-Tuning Degradation: Trajectory Lock-in and Spectral Bifurcation
Resolving the Timestep Scaling Paradox in Spiking Neural Networks with a Timestep-Scalable Neuron Model
SPR-RAFT: Parameter-Efficient Regression-Aware Fine-Tuning for Biomedical LLM Regression
Ski Rental with Distributional Predictions of Unknown Quality
Sparse Relaxed-Lasso Steering: Automatic Sparse Autoencoder Feature Selection for Precise Image Editing
Score-Repellent Monte Carlo: Toward Efficient Non-Markovian Sampler with Constant Memory in General State Spaces
Data Augmentation of Contrastive Learning is Estimating Positive-incentive Noise
On the Provable Suboptimality of Momentum SGD in Nonstationary Stochastic Optimization
FlowSeg: Dynamic Semantic Guidance for LLM-Conditioned Segmentation
From Directions to Regions: Decomposing Activations in Language Models via Local Geometry
A Solver-Free Training Method for Predict-then-Optimize
ModernVBERT: Towards Smaller Visual Document Retrievers
JanusPipe: Efficient Pipeline Parallel Training for Machine Learning Interatomic Potentials
Bregman meets Lévy: Stochastic Mirror Descent with Heavy-Tailed Noise in Continuous and Discrete Time
Social Hippocampus Memory Learning
GI-GCN: Global Interacted Graph Convolutional Networks via Dominant Sets for Graph Classification
Rethinking the Reranker: Boundary-Aware Evidence Selection for Robust Retrieval-Augmented Generation
Learning Self-Interpretation from Interpretability Artifacts: Training Lightweight Adapters on Vector-Label Pairs
Improving ML Attacks on LWE with Data Repetition and Stepwise Regression
SLASH the Sink: Sharpening Structural Attention Inside LLMs
Belief Dynamics Reveal the Dual Nature of In-Context Learning and Activation Steering
Reparameterization Proximal Policy Optimization
DisPPO: Quantile-Based Distributional Reinforcement Learning for Large Language Models
Zero-Shot 3D Question Answering via Hierarchical View-to-Token Transportation
Towards Atoms of Large Language Models
VIBE: Disentangling Social Dynamics via Kinematics-Informed Variational Inference for Behavioral Emotion
Evaluating Object-Centric Models beyond Object Discovery
PartCo: Part-Level Correspondence Priors Enhance Category Discovery
Ambiguous Strategic Classification
Dimension-free convergence of diffusion models for approximate Gaussian mixtures
General and Efficient Steering of Unconditional Diffusion Models
Plan Then Action: High-Level Planning Guidance Reinforcement Learning for LLM Reasoning
LoRDO: Distributed Low-Rank Optimization with Infrequent Communication
Parameter Manifold Purification
Self-Calibrated Consistency can Fight Back for Adversarial Robustness in Vision-Language Models
Divide and Learn: Multi-Objective Combinatorial Optimization at Scale
Local Mechanisms of Compositional Generalization
Reading Between the Tokens: Improving Preference Predictions through Mechanistic Forecasting
Temporal Difference Calibration in Sequential Tasks: Application to Vision-Language-Action Models
Improved Bounds for Reward-Agnostic and Reward-Free Exploration
From Human Labels to Literature: Semi-Supervised Learning of NMR Chemical Shifts at Scale
Great Minds Think Alike: Contextual Tacit Communication for Decentralized LLM-Agent Cooperation
Stochastic Linear Bandits with Parameter Noise
Stop the Flip-Flop: Context-Preserving Verification for Fast Revocable Diffusion Decoding
The Double Dilemma in Multi-Task Radiology Report Generation: A Gradient Dynamics Analysis and Solution
Beyond First-order Asymptotics in Sequential Mean Testing
PhyScene3D: Physically Consistent 3D Interactive Tabletop Scene Generation
TabICLv2: A Better, Faster, Scalable, and Open Tabular Foundation Model
DistMatch: Adaptive Binning via Distribution Matching for Robust Sequential Conformal Prediction
ProphetKV: User-Query-Driven Selective Recomputation for Efficient KV Cache Reuse in Retrieval-Augmented Generation
SemBind: Binding Diffusion Watermarks to Semantics Against Black-Box Forgery Attacks
SyMerge: From Non-Interference to Synergistic Merging via Single-Layer Adaptation
NoiseSDF2NoiseSDF: Learning Clean Neural Fields from Noisy Supervision
On the Limits of LLM Adaptability: Impact of LLM Pre-Training on Annotation Task Performance
L-CUBE: Isolating Long-Context Capacity from Knowledge with Controllable Mutual Information Scaling
JADE: Expert-Grounded Dynamic Evaluation for Open-Ended Professional Tasks
Shared Semantics, Divergent Mechanisms: Unsupervised Feature Discovery by Aligning Semantics and Mechanisms
Neural Control: Adjoint Learning Through Equilibrium Constraints
Anchor-Final Self-Supervision Drives Hallucination-Aware Optimization in Large Vision-Language Models
Adapting to Evolving Graphs: A Scalable Framework for Dynamic Coarsening
ObjEmbed: Towards Universal Multimodal Object Embeddings
On the Entropy Dynamics in Reinforcement Fine-Tuning of Large Language Models
Curating the Future: A Scalable Recipe for Training Open-Ended Forecasters
CE$^4$L: Continual Ego, Exo, and Ego-Exo Learning
Minimax Optimal Strategy for Delayed Observations in Online Reinforcement Learning
MDN: Parallelizing Stepwise Momentum for Delta Linear Attention
From Winning to Understanding: A Diagnostic Long-Horizon RTS Benchmark for LLMs
Zero-Shot Text-to-Motion Evaluation using Video Language Models
Mitigating Error Accumulation in Continuous Navigation via Memory-Augmented Kalman Filtering
Dichotomy of Feature Learning and Unlearning: Fast-Slow Analysis on Neural Networks with Stochastic Gradient Descent
Near-Universal Multiplicative Updates for Nonnegative Einsum Factorization
CG-MLLM: Captioning and Generating 3D content via Multi-modal Large Language Models
Abductive Reasoning with Probabilistic Commonsense
Unveiling And Addressing Dimensional Collapse In Vector Quantization Models Via Codebook Regularization
Training with Honeypots: Reshaping How LLMs Fail Under Adversarial Attacks
Recontextualization Mitigates Specification Gaming Without Modifying the Specification
CORAL: Uncertainty-Aware Regulation of Exposure Concentration in Recommender Systems
Model Fusion via Retrofitting
SPARKLING: Balancing Signal Preservation and Symmetry Breaking for Width-Progressive Learning
CodeClash: Benchmarking Goal-Oriented Software Engineering
LARFT: Closing the Cognition-Action Gap for Length Instruction Following in Large Language Models
SC$^{2}$-WM: A Self-Correcting World Model with Closed-Loop Feedback for Vision-and-Language Navigation in Continuous Environments
Adaptive Preconditioners Trigger Loss Spikes in Adam
Ego3S: Select, Strengthen, and Synchronize for Efficient Egocentric Reasoning
MESA: Improving MoE Safety Alignment via Decentralized Expertise
DADP: Domain Adaptive Diffusion Policy
NaviCache: Test-Time Self-Calibration Caching for Video Generation
Latent Thoughts Tuning: Bridging Context and Reasoning with Fused Information in Latent Tokens
Kinematics-Driven Gaussian Shape Deformation for Blurry Monocular Dynamic Scenes
Private Learning with Public Feature Conditioning
Unlocking Speech–Text Compositional Powers: Instruction-Following Speech Language Models without Instruction Tuning
Latent Reasoning in TRMs is Secretly a Policy Improvement Operator
Consistent Diffusion Language Models
Rotation-Invariant Spherical Watermarking via Third-Order SO(3) Representation Coupling
TSRBench: A Comprehensive Multi-task Multi-modal Time Series Reasoning Benchmark for Generalist Models
Synergistic Intra- and Cross-Layer Regularization Losses for MoE Expert Specialization
Adaptively Grouped Contextual Bandits for Heterogeneous Human-AI Decision Making with Conformal Prediction Sets
Federated Graph Learning via Structure-Aware Fusion Using a Kalman Framework with Learnable Dynamics
Learning More from Less: Unlocking Internal Representations for Benchmark Compression
Online Packet Scheduling with Deadlines and Learning
R2-Router: A New Paradigm for LLM Routing with Reasoning
Learning Long Range Spatio-Temporal Representations over Continuous Time Dynamic Graphs with State Space Models
Improving Topic Modeling by Distilling Soft Labels from Language Models
IAPO: Information-Aware Policy Optimization for Token-Efficient Reasoning
Spherical SO(3) Equivariant Local Attention
Credit Assignment via Neural Manifold Noise Correlation
Information-Geometric Adaptive Sampling for Graph Diffusion
Structure-Preserving Learning Improves Geometry Generalization in Neural PDEs
Spatial Conformal Inference through Localized Quantile Regression
Taming I2V models for Image HOI Editing: A Cognitive Benchmark and Agentic Self-Correcting Framework
VideoSEAL: Mitigating Evidence Misalignment in Agentic Long Video Understanding by Decoupling Answer Authority
RePo: Language Models with Context Re-Positioning
SHERPA: Fine-tuning Segment Anything Models with Task-relevant Guidance
CAMP: Coherent Alignment of Multimodal Prototypes for Explainable Complementary Learning
Probabilistic Robustness Certificates against Adversarial Attacks
New Algorithms for Fully-Dynamic k-center with Outliers
A Coin Flip for Safety: LLM Judges Fail to Reliably Measure Adversarial Robustness
From Guessing to Placeholding: A Cost-Theoretic Framework for Uncertainty-Aware Code Completion
SecCodePRM: A Process Reward Model for Code Security
OSF: On Pre-training and Scaling of Sleep Foundation Models
Reinforced Sequential Monte Carlo for Amortised Sampling
Breaking the Simplification Bottleneck in Amortized Neural Symbolic Regression
Direct Flow Q-Learning
Prompt Optimization with Minimal Unlabeled Input via Meta-Reasoning
Omni-fMRI: A Universal Atlas-Free fMRI Foundation Model
Alignment Risks from Capability-Seeking RL Training
A Decision-Theoretic View of Test-Time Training: When, How Far, and Which Directions to Adapt
Learning to Reconfigure: Configuration-Control Co-optimization of Reconfigurable Robots for Heterogeneous Locomotion
Not All Prefills Are Equal: PPD Disaggregation for Multi-turn LLM Serving
Structure-Aware Consistency Priors for Shape from Polarization in Complex Media
A Diffusive Classification Loss for Learning Energy-based Generative Models
HEARTS: Benchmarking LLM Reasoning on Health Time Series
Discounted Beta–Bernoulli Reward Estimation for Sample-Efficient Reinforcement Learning with Verifiable Rewards
Distributional Inverse Reinforcement Learning
ReJump: A Tree-Jump Representation for Analyzing and Improving LLM Reasoning
Are Object-Centric Representations Better at Compositional Generalization?
Escaping the Subspace Trap: The Role of Optimizer Geometry in Model Width Expansion
Probability of Matching for Batch Multi-Objective Bayesian Optimization
Prompt Tuning for CLIP on the Pretrained Manifold
Contrastive Symbolic Regression: Aligned Representations, Adaptive Prediction, and Diverse Ensembles
Multi-Label Learning with Contrastive Cluster Self-Supervision for 3D Hierarchical Semantic Segmentation
Gradient Inversion Attacks Beyond SGD
DB-KSVD: Scalable Alternating Optimization for Disentangling High-Dimensional Embedding Spaces
Posterior Sampling Reinforcement Learning with Gaussian Processes for Continuous Control: Sublinear Regret Bounds for Unbounded State Spaces
Dynamic Linear Attention
Implicit Intelligence - Evaluating Agents on What Users Don’t Say
R2R2: Robust Representation for Intensive Experience Reuse via Redundancy Reduction in Self-Predictive Learning
SceneSmith: Agentic Generation of Simulation-Ready Indoor Scenes
Bring Future Vision: Dynamic Computation Allocation Guided by Lightweight Feature Forecaster
From Basis to Basis: Gaussian Particle Representation for Interpretable PDE Operators
Gaussian Mean Field Variational Inference can Overestimate Predictive Variance
Dynamic Symmetric Point Tracking: Tackling Non-ideal Reference in Analog In-memory Training
Discrete Diffusion Samplers and Bridges: Off-Policy Algorithms and Applications in Latent Spaces
Deep Discriminative Structure Proxy Hashing for Cross-modal Retrieval
MoCo-EA: Exploiting Adversarial Mode Connectivity for Efficient Evolutionary Attacks
Accelerated Multiple Wasserstein Gradient Flows for Multi-objective Distributional Optimization
Trainable Nonexpansive Denoisers for Contractive Image Reconstruction
Think-Then-Generate: Reasoning-Aware Text-to-Image Diffusion with LLM Encoders
Giving Sensors a Voice: Multimodal JEPA for Semantic Time-Series Embeddings
Unifying Stacking and Cascading for Efficient Ensemble Inference
Beyond Accuracy: Latent Perturbations for Cognitive-Aware Diagnosis
SMILE: Extended Deep Submodular Function-Based Instruction and In-context Learning Demonstration Selection
Incorporating Importance Weighting in Optimal Transport Based Domain Alignment
Knowing When to Quit: A Principled Framework for Dynamic Abstention in LLM Reasoning
A General Framework for Fair and Robust Regression
USE: A Unified Self-Ensembling Framework for Test-Time Prompt Tuning
The Devil is in the Spectrum: Mitigating Representation Collapse in LLMs via Topologically Regularized Side-Path
Step-Resolved Data Attribution for Looped Transformers
Mitigating Premature Exploitation in Particle-based Monte Carlo for Inference-Time Scaling
AutoRPA: Efficient GUI Automation through LLM-Driven Code Synthesis from Interactions
A Graphop Analysis of Graph Neural Networks on Sparse Graphs: Generalization and Universal Approximation
Rethinking Gating Mechanism in Sparse MoE: Handling Arbitrary Modality Inputs with Confidence-Guided Gate
REViT: Roto-reflection Equivariant Convolutional Vision Transformer
Graph is a Natural Regularization: Revisiting Vector Quantization for Graph Representation Learning
A Studentized Spherical Harmonics–Based Nonparametric Two-Sample Test for Compositional and Directional Data
PlotCraft: Pushing the Limits of LLMs for Complex and Interactive Data Visualization
Efficient Test-Time Scaling via Hierarchical Search and Self-Verification for Discrete Diffusion Language Models
Bringing Code ALIVE: Optimizing Interactive Frontend Mini-Games via Automated Play and Reinforcement Learning at Scale
One-Shot Weighted Ensemble Estimation for Federated Quantile Regression: Optimal Statistical Guarantees under Heterogeneous Structured Data
Towards Understanding Adam Convergence on Highly Degenerate Polynomials
FT-Dojo: Towards Autonomous LLM Fine-Tuning with Language Agents
EvoGM: Learning to Merge LLMs via Evolutionary Generative Optimization
On the Convergence Rate of LoRA Gradient Descent
GRPO-based Cluster Decision Agent for Unknown-$\boldsymbol{K}$ Multi-view Clustering
Adaptive Reinforcement Learning for Unobservable Random Delays
InteractScience: Programmatic and Visually-Grounded Evaluation of Interactive Scientific Demonstration Code Generation
Multi-Adapter Representation Interventions via Energy Calibration
Taming Stochastic Gradient Descent: Almost Sure Convergence and Saddle-Point Avoidance under $(L_{0},L_{1})$-Smoothness
BubbleSpec: Turning Long-Tail Bubbles into Speculative Rollout Drafts for Synchronous Reinforcement Learning
EEmo-Logic: A Unified Dataset and Multi-Stage Framework for Comprehensive Image-Evoked Emotion Assessment
SEDRAS: Symbolically Evaluated Deep Research And Science
LIMSSR: LLM-Driven Sequence-to-Score Reasoning under Training-Time Incomplete Multimodal Observations
Formalizing and Falsifying Causal Pathways of Rare Events
Differentially Private Cross-Silo Recommendation from Implicit Feedback
Discovering Interpretable Algorithms by Decompiling Transformers to RASP
Automated Formal Proofs of Combinatorial Identities via Wilf–Zeilberger Guidance and LLMs
Multi-agent imitation learning with function approximation: linear Markov games and beyond
ASTRA: Communication-Efficient Acceleration for Multi-Device Transformer Inference
See More, Forecast Better and Faster: Enhancing Time Series Foundation Models via Inference-Time Plug-and-Play Downsampling
How Does the Pretraining Distribution Shape In-Context Learning? A Fundamental Trade-Off
Fast and Scalable Analytical Diffusion
DLEBench: Evaluating Small-scale Object Editing Ability for Instruction-based Image Editing Model
Scalable Traffic Signal Control with Shared Policy Framework
On Information Self-Locking in Reinforcement Learning for Active Reasoning of LLM agents
HexGen-3: A Fully Disaggregated LLM Serving Framework with Fine-Grained Heterogeneous Resource Autoscaling
UltraLIF: Fully Differentiable Spiking Neural Networks via Ultradiscretization and Max-Plus Algebra
Concept Concentration for Faithful Representation Intervention
On the Separability of Information in Diffusion Models
Sheaf Neural Networks on SPD Manifolds: Second-Order Geometric Representation Learning
SAQNN: Spectral Adaptive Quantum Neural Network as a Universal Approximator
Enhancing Membership Inference Attacks on Diffusion Models from a Frequency-Domain Perspective
TodoEvolve: Learning to Architect Agent Planning Systems
Generalist Graph Anomaly Detection via Prototype-Based Distillation
Differentially Private Range Subgraph Counting
SaTeen: Learning Structural Alignment for Continual Test-Time Adaptation
ForensicConcept: Transferable Forensic Concepts for AIGI Detection
Geometric Decoupling: Diagnosing the Structural Instability of Latent
Reviving Error Correction in Modern Deep Time-Series Forecasting
Spectral Flow Matching: Stabilizing Stochastic GFlowNets via Frequency-Domain Regularization
From Rashomon Theory to PRAXIS: Efficient Decision Tree Rashomon Sets
User-Aware Active Knowledge Acquisition for Emotional Support Dialogue
GEM: Geometric Erasure by Contrastive Velocity Matching in Rectified Flows
Breaking the Reference Bottleneck via Learning to Rewrite Conversational Queries without Gold Reference Passages
How (Not) to Hybridize Neural and Mechanistic Models for Epidemiological Forecasting
HaloProbe: Bayesian Detection and Mitigation of Object Hallucinations in Vision-Language Models
Symmetry Reveals the In-Context Classifier: Transformers Implement Mean-Shift Dynamics
A Tale of Two Problems: Multi-Task Bilevel Learning Meets Equality Constrained Multi-Objective Optimization
SpaEF: Spatially Resolved Transcriptomics Data Element-Wise Denoising Framework Powered by Large Models
AliMark: Enhancing Robustness of Sentence-Level Watermarking Against Text Paraphrasing
DecFus: Decentralized Layer-wise Fusion with Dynamic Exploration and Exploitation
EnterpriseOps-Gym: Environments and Evaluations for Stateful Agentic Planning and Tool Use in Enterprise Settings
What is Missing? Explaining Neurons Activated by Absent Concepts
Subspace-Aware Feature Reshaping for Open-Set Graph Class-Incremental Learning
Scaling Prompt Synthesis for Large Language Model Reasoning
Provable Accuracy Collapse of Embedding-Based Representations under Dimensionality Mismatch
ConFu: Contemplate the Future for Better Speculative Sampling
ProcMEM: Learning Reusable Procedural Memory from Experience via Non-Parametric PPO for LLM Agents
XYZFlow: Scaling Multidimensional Shortcut Flows for Efficient Generative Modeling
Full-Batch Gradient Descent Outperforms One-Pass SGD: Sample Complexity Separation in Single-Index Learning
From Perception to Planning: Evolving Ego-Centric Task-Oriented Spatiotemporal Reasoning via Curriculum Learning
A Minimal Agent for Automated Theorem Proving
Layer-Centric Factors of Variation Disentanglement for Task- and Model-Agnostic Generalization
DPsurv: Dual-Prototype Evidential Fusion for Uncertainty-Aware and Interpretable Whole Slide Image Survival Prediction
Reinforcing Real-world Service Agents: Balancing Utility and Cost in Task-oriented Dialogue
PFT: Phonon Fine-tuning for Machine Learned Interatomic Potentials
Maximizing Mutual Information Between Prompt and Response Improves LLM Performance With No Additional Data
Asymptotic Universal Alignment: A New Alignment Framework via Test-Time Scaling
Online Change Point Detection for Multivariate Inhomogeneous Poisson Processes Time Series
Source-Free Open-World RF Fingerprint Identification
Offline Multi-Agent Reinforcement Learning via Sequential Score Decomposition
GIPO: Gaussian Importance Sampling Policy Optimization
GameVerse: Can Vision-Language Models Learn from Video-based Reflection?
Hyperparameter Transfer Laws for Non-Recurrent Multi-Path Neural Networks
Vulnerable Agent Identification in Large-Scale Multi-Agent Reinforcement Learning
Stochastic Gradient Methods under Heavy-Tailed Noises in Weakly Convex Optimization
Can VLMs Diagnose and Recover from VLA Manipulation Faults?
MaMi-HOI: Harmonizing Global Kinematics and Local Geometry for Human-Object Interaction Generation
Learning Task-Sufficient World Models by Synergizing Agentic Exploration and Structured Modeling
FiRE: Fine-grained Ranking Evaluation for Machine Translation
Just-In-Time Reinforcement Learning: Continual Learning in LLM Agents Without Gradient Updates
Logarithmic Switching Regret for Online Convex Optimization
HIAL: Towards Semantics-Aware Hypergraph Active Learning via Dual-Perspective Information Maximization
Capacity without Access: Reinterpreting the Mid-Depth Spectral Plateau in LLMs
Beyond Test-Time Memory: State-Space Optimal Control for LLM Reasoning
Path-Coupled Bellman Flows for Distributional Reinforcement Learning
Who can we trust? LLM-as-a-jury for Comparative Assessment
Efficient Online Variational Estimation via Monte Carlo Sampling
AOEPT: Breaking the Implicit Modality-Reduction Bottleneck in Modality-Missing Prompt Tuning
Beyond the Final Answer: Evaluating the Reasoning Trajectories of Tool-Augmented Agents
On the Relationship Between Activation Outliers and Feature Death in Sparse Autoencoders
SCOPE: Evolving Symbolic World for Planning in Open-Ended Environments
Achieving Structurally Robust Gromov Wasserstein Distance via Adaptive Dual-Mask
BARRED: Synthetic Training of Custom Policy Guardrails via Asymmetric Debate
PerturbDiff: Functional Diffusion for Single-Cell Perturbation Modeling
HASTE: Hardware-Aware Dynamic Sparse Training for Large Output Spaces
PatternKV: Flattening KV Representation Expands Quantization Headroom
Optimal Pricing for Data-Augmented AutoML Marketplaces
Understanding Data Temporality Impact on Large Language Models Pre-training
Provable Benefits of RLVR over SFT for Reasoning Models: Learning to Backtrack Efficiently
Scaling Unsupervised Multi-Source Federated Domain Adaptation through Group-Wise Discrepancy Minimization
Inside the Visual Mind: Neuroscience-Motivated Concept Circuits for Interpreting and Steering Vision Transformers
TrustworthyQENN: A Quantum Evidential Neural Network Based on Complex-Valued Contrastive Learning for Uncertainty Pattern Classification
BEAT: Tokenizing and Generating Symbolic Music by Uniform Temporal Steps
Ideal Attribution and Faithful Watermarks for Language Models
Don't Forget Why You Started: Tackling Dual Forgetting in Vision-Language Continual Learning
Designing Observation and Action Models for Efficient Reinforcement Learning with LLMs
A Mechanistic Analysis of Sim-and-Real Co-Training in Generative Robot Policies
Questioning the Coverage-Length Metric in Conformal Prediction: When Shorter Intervals Are Not Better
A Behavioural and Representational Evaluation of Goal-Directedness in Language Model Agents
Cram Less to Fit More: Training Data Pruning Improves Memorization of Facts
Erased but Not Forgotten: How Backdoors Compromise Concept Erasure
Understanding the Gaps in Satisficing Bandits
How can we assess human-agent interactions? Case studies in software agent design
Non-Uniform Noise-to-Signal Ratio in the REINFORCE Policy-Gradient Estimator
APE-Bench: Evaluating Automated Proof Engineering for Formal Math Libraries
Compositional Transduction with Latent Analogies for Offline Goal-Conditioned Reinforcement Learning
Empirical Gaussian Processes
Towards Complete Multi-Agent Coordination Policy Learning via Denoising Maximum Entropy Optimization
Discontinuous Galerkin Neural Operator for Pathology Defocus Deblurring
Front-Loaded Robust Conformal Prediction: Heavy Calibration, Minimal Test-Time Cost
Persuasive Privacy
Euclean: Automated Geometry Problem Formalization with Unified Verification in Lean
AugMask: Training Diffusion Models on Incomplete Tabular Data via Stochastic Augmentation and Masking
Reliable Confidence Alignment for Generalized Category Discovery
Multimodal Scaling Laws for Task & Data-Optimized Models of Visual Cortex
MedScope: Incentivizing "Think with Videos" for Clinical Reasoning via Coarse-to-Fine Tool Calling
Beyond Additive Decompositions: Interpretability Through Separability
Dyn-VPP: Video Prediction Policy Optimization for Improved Visual Dynamics
UB-SMoE: Universally Balanced Sparse Mixture-of-Experts for Resource-adaptive Federated Fine-tuning of Foundation Models
MedMosaic: A Challenging Large Scale Benchmark of Diverse Medical Audio
Learning Protein Structure-Function Relationships through Knowledge-guided Representation Decomposition
Seeing Symbols, Missing Structure: A Real-World Handwritten Mathematical Expression Recognition Benchmark for Large Models
ImpQuant: Fine-Grained Importance-Aware Quantization for Large Vision-Language Models
Identifying dependent components from multi-domain linear mixtures
Causal Attention with Lookahead Keys
Exploring 3D Dataset Pruning
FedQueue: Queue-Aware Federated Learning for Cross-Facility HPC Training
Robust Learning via Nested Distributionally Robust Optimization
ALSO: Adversarial Online Strategy Optimization for Social Agents
Logical Guidance for the Exact Composition of Diffusion Models
PSBench: Editing Image via GUI Agents in Photoshop
MALICE: Memory-aware Loop Invariants Generation on Symbolic Execution Traces
Breaking Dual Bottlenecks: Evolving Unified Multimodal Models into Self-Adaptive Interleaved Visual Reasoners
TiMi: Empower Time Series Transformers with Multimodal Mixture of Experts
TVI-CoT: Text-Visual Interleaved Chain-of-Thought Reasoning for Multimodal Understanding
Collaborative and Efficient Fine-tuning: Leveraging Task Similarity
SLIP-RS: Structured-Attribute Language-Image Pre-Training for Remote Sensing Object Detection
Rethinking Instruction Drift as a Sampling Error: SNR-Aware Power Distributions for Long-Horizon Robotic Planning
FedScar: Correcting Geometric Bias for Flatness-Consistent Federated Learning
In-Context Learning as Rate–Distortion Optimization
NNiT: Width-Agnostic Neural Network Generation with Structurally Aligned Weight Spaces
Safety Generalization Under Distribution Shift in Safe Reinforcement Learning: A Diabetes Testbed
Safe In-Context Reinforcement Learning
ParalESN: Enabling parallel information processing in Reservoir Computing
Emergence of Exploration in Policy Gradient Reinforcement Learning via Retrying
Bridging Local–Global Dissonance: Learning from Compressive Measurements for Hyperspectral Reconstruction
Budgeted Active Experimentation for Treatment Effect Estimation from Observational and Randomized Data
Hunt Instead of Wait: Evaluating Deep Data Research on Large Language Models
Synthesizable Molecular Generation via Soft-constrained GFlowNets with Rich Chemical Priors
scDataset: Scalable Data Loading for Deep Learning on Large-Scale Single-Cell Omics
Efficient Bayesian Inference from Noisy Pairwise Comparisons
EDCO: Dynamic Curriculum Orchestration for Domain-specific Large Language Model Fine-tuning
Anti-Aliasing Matters: A Dynamic Network for Time Series Forecasting
Calibrated Test-Time Guidance for Bayesian Inference
AdLift: Lifting Adversarial Perturbations to Safeguard 3D Gaussian Splatting Assets Against Instruction-Driven Editing
A Single Layer to Explain Them All: Understanding Massive Values in Large Language Models
Efficient and Safe Molecular Assembly via Reinforcement Learning and Constraint Solving
Dual-Stream Diffusion for World-Model Augmented Vision-Language-Action Model
Does Reasoning Improve Seeing? Understanding When Vision-Language Models Benefit from Thinking
API: Adaptive Prototype Imputation for Incomplete Multimodal Sentiment Analysis
Mitigating Conversational Inertia in Multi-Turn Agents
Training-Free Adversarial Robustness in Computational MRI
The Latent Guardian: Defending Collaborative Perception via Feature-Level Consistency Verification
From Prompts to Tokens: Internalizing Causal Supervision in Vision-Language Model for Multi-Image Causal Reasoning
DiffuReason: Enhancing Reasoning Ability for Diffusion Language Models via Monte Carlo Tree Search
Reverse-Engineering Model Editing on Language Models
Decoupling Universal Laws and Environmental Heterogeneity: A Physics-Inspired Framework for Robust Spatio-Temporal Forecasting
Learning High-Dimensional Parity Functions with Product Networks using Gradient Descent
Efficient Multi-round LLM Inference over Disaggregated Serving
From Parameter Dynamics to Risk Scoring: Quantifying Sample-Level Safety Degradation in LLM Fine-tuning
STAND: Self-Aware Precondition Induction for Interactive Task Learning
Mitigating Noise-Induced Layout Priors for Object Counting in Diffusion Models
Enhancing Reasoning for Diffusion LLMs via Distribution Matching Policy Optimization
TAGRPO: Boosting GRPO on Image-to-Video Generation with Direct Trajectory Alignment
Arboreal Neural Network
Theoretical Challenges in Learning for Branch-and-Cut
SRPO: Self-Reflective Policy Optimization for Long-Horizon Reasoning
TransNormal: Dense Visual Semantics for Diffusion-based Transparent Object Normal Estimation
SABER: Continual Learning with Representation Conflict Management
Mind Dreamer: Untethering Imagination via Active Causal Intervention on Latent Manifolds
MEAL: A Benchmark for Continual Multi-Agent Reinforcement Learning
Tractable Expected Information Gains for Exponential Family Posteriors
MatchFixAgent: Language-Agnostic Autonomous Repository-Level Code Translation Validation and Repair
ConTSG-Bench: A Unified Benchmark for Conditional Time Series Generation
MAPS: Memory-Aware Predictive Scheduling Framework for Large Language Model Serving
Awakening Visual Reasoning: Mitigating Post-Training Failure in Vision-Text Compression
Threat2Traffic: Multi-Agent Environment Synthesis for Malware Traffic Generation from Threat Intelligence
On the Power of (Approximate) Reward Models for Inference-Time Scaling: Sequential Monte Carlo and Beyond
SCOUT: Active Information Foraging for Long-Text Understanding with Decoupled Epistemic States
Detecting Contextual Hallucinations in Large Language Models with Frequency-Aware Attention
Minimum Distance Summaries for Robust Neural Posterior Estimation
UniSparse: Combining Weight Pruning and Spike Sparsification in Spiking Neural Networks
Learning Coupled Continuous-Time Latent Dynamics from Irregular Events
Conformal Calibration Transfer
PRM-PBE: Process Reward Model for Reinforcement Learning in Programming-by-Example
From Historical Patches to Repair Plans: Outcome-Conditioned Reasoning for Repository-Level Program Repair
MECAT: A Multi-Experts Constructed Benchmark for Fine-Grained Audio Understanding Tasks
Mesh Field Theory: Port–Hamiltonian Formulation of Mesh-Based Physics
What LLMs Explain Is Not What They Believe: Evaluating Explanation Sufficiency Under Models' Own Input Beliefs
Hair-Trigger Alignment: Black-Box Evaluation Cannot Guarantee Post-Update Alignment
Neural Implicit Action Fields: From Discrete Waypoints to Continuous Functions for Vision-Language-Action Models
CGRiC: Compositional Risk Certification for Structured LLM Outputs
KANFIS: A Neuro-Symbolic Framework for Interpretable and Uncertainty-Aware Learning
Detecting Fluent Optimization-Based Adversarial Prompts via Sequential Entropy Changes
Advantage Collapse in Group Relative Policy Optimization: Diagnosis and Mitigation
QHyer: Q-conditioned Hybrid Attention-mamba Transformer for Offline Goal-conditioned RL
Facts in Stats: Impacts of Pretraining Diversity on Language Model Generalization
Weakly Supervised Cross-Modal Learning for 4D Radar Scene Flow Estimation
Profiling the Irrational Agent: Cognitive Modeling of LLM Behaviors in Sequential Jailbreaks
On the Theoretical Limitations of Embedding-based Link Prediction
LazyAttention: Efficient Retrieval-Augmented Generation with Deferred Positional Encoding
Online Fair Division with Additional Information
Real-Time Visual Attribution Streaming in Thinking Model
OnePO: Direct One-stage Policy Optimization for SFT-free Domain Adaptation
Efficient Bilevel Optimization for CKA-Guided MoE Upcycling
A Stronger Benchmark for Online Bilateral Trade: From Fixed Prices to Distributions
TN-SHAP-G: Graph-Structured Tensor Network Surrogates for Shapley Values and Interactions
Iterative Robust Satisficing: Minimizing Performance Degradation Under Distribution Shift
Adaptive Physics Transformer with Fused Global-Local Attention for Subsurface Energy Systems
Language Model Networks: Supervision-Efficient Learning through Dense Communication
LoRA-DA: Data-Aware Initialization for Low-Rank Adaptation via Asymptotic Analysis
Letting Trajectories Spread: Quality-Preserving Control for Diverse Flow Matching
Spiked-CFR: Causal Representation Learning from LLMs via Wasserstein Projection Pursuit
Offline Reinforcement Learning with Generative Trajectory Policies
Estimating Correlation Clustering Cost in Node-Arrival Stream
FlowPET: Physics-Informed Symplectic Flow Matching for Low-Count PET Reconstruction
Foresee-to-Ground: From Predictive Temporal Perception to Evidence-Driven Reasoning for Video Temporal Grounding
Prompt Injection as Role Confusion
Accurate Evaluation of Quickest Changepoint Detectors via Non-parametric Survival Analysis
Automatic Pruning Discovery for Large Language Models
Agentic Framework for Epidemiological Modeling
Thinking in Scales: Accelerating Gigapixel Pathology Image Analysis via Adaptive Continuous Reasoning
Unlocking the Potential of Continual Model Merging: An ODE Perspective
Thoughtbubbles: an Unsupervised Method for Parallel Thinking in Latent Space
Controlled LLM Training on Spectral Sphere
Mitigating Bias in Locally Constrained Decoding via Tractable Proposals
Seeing is Solving: Unlocking Efficient Multimodal RL via View Alignment
CoGenCast: A Coupled Autoregressive–Flow Generative Framework for Time Series Forecasting
GIFT: Bootstrapping Image-to-CAD Program Synthesis via Geometric Feedback
Beyond VLM-Based Rewards: Diffusion-Native Latent Reward Modeling
Hölder++: Improving Quality-Coherence Trade-off in Multimodal VAEs
VALUEFLOW: Toward Pluralistic and Steerable Value-based Alignment in Large Language Models
Query-efficient model evaluation using cached responses
Sinkhorn Normalization of Diffusion Kernels
Design Linear Constrained Neural Layers with Implicit Convex Optimization
LK Losses: Direct Acceptance Rate Optimization for Speculative Decoding
Unbiased Reward Modeling from Implicit Feedback for LLM Alignment
Mean Flow Distillation: Robust and Stable Distillation for Flow Matching Models
On the Interaction of Batch Noise, Adaptivity, and Compression, under $(L_0,L_1)$-Smoothness: An SDE Approach
Inducing Overthink: Hierarchical Genetic Algorithm-based DoS Attack on Black-Box Large Language Reasoning Models
Success-Conditioning as Policy Improvement: The Optimization Problem Solved by Imitating Success
Structured Multi-modal Graph Disentanglement for Psychiatric Diagnosis
VR-Thinker: Boosting Multimodal Reward Models through Think with Image Reasoning
Data Difficulty and the Generalization–Extrapolation Tradeoff in LLM Fine-Tuning
Distribution Alignment for One-Shot Federated Learning via Optimal Transport
GLAD: Bidirectional Structure-Attribute Alignment via Latent Graph Diffusion Models
Dynamic Fractal Mamba: A Neural Renormalization Group Flow for Scale-Invariant Sequence Modeling
Opt-Verifier: Unleashing the Power of LLMs for Optimization Modeling via Dual-Side Verification
TaskLoom: Weaving Knowledge Across Tasks in World Models
From Shortcuts to Reasoning: Robust Post-Training of Theory of Mind with Reinforcement Learning
CountsDiff: A diffusion model on the natural numbers for generation and imputation of count-based data
On the Emergence of Implicit Curriculum in RLVR Learning Dynamics
$R^3$DAO: Reactive Recovery and Reconstruction for Long-horizon Data Agent Orchestration
Mind the State: Towards Unified, Context-Aware EEG-to-fMRI Synthesis
ReaForest: Fostering Generative Video Reasoning for Spatial Planning
Test-Time Learning of Causal Structure from Interventional Data
On the Ability of Transformers to Verify Plans
Cert-LAS: Toward Certified Model Ownership Verification for Text-to-Image Diffusion Models via Layer-Adaptive Smoothing
Combinatorial Sparse PCA Beyond the Spiked Identity Model
SWE-Compass: Towards Unified Evaluation of Agentic Coding Abilities for Large Language Models
Fully Zero-Shot Image Dehazing
Spectral Bridge Variational Inference: Dynamic LoRA via Bures-Wasserstein Gradient Flows
Exploring Accurate and Transparent Domain Adaptation in Predictive Healthcare via Concept-Grounded Orthogonal Inference
BrokenMath: A Benchmark for Sycophancy in Theorem Proving with LLMs
Recovering Hidden Reward in Diffusion-Based Policies
Trustworthy Federated Label Distribution Learning under Annotation Quality Disparity
Long Live The Balance: Information Bottleneck Driven Tree-based Policy Optimization
$\texttt{FHAIM}$: Fully Homomorphic AIM for Private Tabular Synthetic Data Generation
D-CORE: Incentivizing Task Decomposition in Large Reasoning Models for Complex Tool Use
Recovering Policy-Induced Errors: Benchmarking and Trajectory Synthesis for Robust GUI Agents
Flow Matching Calibration for Simulation-Based Inference under Model Misspecification
MVI-Bench: A Comprehensive Benchmark for Evaluating Robustness to Misleading Visual Inputs in LVLMs
Towards Scalable and Consistent 3D Editing
EpiCoCo: De Novo Epitope Generation via MHC-Context Co-Modeling and Contrastive Affinity Guidance
Probabilistic Performance Guarantees for Multi-Task Reinforcement Learning
MidSteer: Optimal Affine Framework for Steering Generative Models
PortraitRL: Reinforcement Learning for Personalized Portrait Pose Transfer with Multi-Objective Reward Modeling
Decision-focused Sparse Tangent Portfolio Optimization
Unveiling the Structure of Do-Calculus Reasoning via Derivation Graphs
Complexity of Decentralized Optimization with Mixed Affine Constraints
Protein Language Model Embeddings Improve Generalization of Implicit Transfer Operators
Learning to Move Before Learning to Do: Task-Agnostic pretraining for VLAs
JADE: Bridging the Strategic-Operational Gap in Dynamic Agentic RAG
Accelerated Dual Method for Distributed Optimization: An Inexact-Gradient View of Local Updates
OmniAID: Decoupling Semantic and Artifacts for Universal AI-Generated Image Detection in the Wild
Speech-Audio Compositional Attacks on Multimodal LLMs and Their Defense with SALMONN-Guard
DiffCrossGait: Trajectory-Level Alignment for 2D-3D Cross-Modal Gait Recognition via Latent Diffusion
LILO: Bayesian Optimization with Natural Language Feedback
Let the Prototype Guide You: Robust Aggregation of Sparse Multi-Class Annotations via Annotator Prototype Learning
Local Linearity of LLMs Enables Activation Steering via Model-Based Linear Optimal Control
How2Everything: Mining the Web for How-to Procedures to Evaluate and Improve LLMs
CausalXRL: Explainable Reinforcement Learning through Causal Graph Reasoning
AesFormer: Transform Everyday Photos into Beautiful Memories
Intentional Updates for Streaming Reinforcement Learning
LaRA-Fusion: Latent-Robust Adaptation via Dual-Loop Constraints for Infrared and Visible Image Fusion
ImpText: A Benchmark and Tool-Augmented Framework for Implicit Text Reasoning
Training-Free Bayesian Filtering with Generative Emulators
GDPO: Group reward-Decoupled Normalization Policy Optimization for Multi-reward RL Optimization
Meta Flow Maps enable scalable reward alignment
Token Sample Complexity of Attention
GIST: Targeted Data Selection for Instruction Tuning via Coupled Optimization Geometry
Efficient-DLM: From Autoregressive to Diffusion Language Models, and Beyond in Speed
HARD-KV: Head-Adaptive Regularization for Decoding-time KV Compression
Dynamics Within Latent Chain-of-Thought: An Empirical Study of Causal Structure
Envisioning Beyond the Few: Disentangled Semantics and Primitives for Few-Shot Atypical Layout-to-Image Generation
ToolOrchestra: Elevating Intelligence via Efficient Model and Tool Orchestration
SONAR: Spectral‑Contrastive Audio Residuals for Generalizable Deepfake Detection
Self-Distilled Reasoner: On-Policy Self-Distillation for Large Language Models
Unsupervised Neural Langevin Sampler for Mixed Integer Linear Programming
From Representation to Action: A Unified Laplacian Framework for Spatial Representation and Path Planning
Graph of States: Solving Abductive Tasks with Large Language Models
IPMark: A Sentence-Level Watermark for LLMs with Hierarchical Personalization and Efficient Detection
SafeDec: Constrained Decoding for Safe Autoregressive Generalist Robot Navigation Policies
CLARITree: Cholesky and Lookahead Accelerations for Regression with Interpretable Piecewise Linear Trees
Learning in Bayesian Stackelberg Games With Unknown Follower's Types
Universal Reasoner: A Single, Composable Plug-and-Play Reasoner for Frozen LLMs
DyPE: Dynamic Position Extrapolation for Ultra High Resolution Diffusion
SPR: A Structured Prompt Refinement Network for Modality Missing
Dynamic TMoE: A Drift-Aware Dynamic Mixture of Experts Framework for Non-Stationary Time Series Forecasting
Two-dimensional quantization for geometry-aware audio coding
How High is ‘High’? Rethinking the Roles of Dimensionality in Topological Data Analysis and Manifold Learning
Escaping the Mode: Multi-Answer Reinforcement Learning in LMs
Optimal Bayesian Stopping for Efficient Inference of Consistent LLM Answers
Adaptive Momentum and Nonlinear Damping for Neural Network Training
Tailoring Strictly Proper Scoring Rules for Downstream Tasks: An Application to Causal Inference
Platonic Transformers: A Solid Choice For Equivariance
Principled Synthetic Data Enables the First Scaling Laws for LLMs in Recommendation
Divergence Decoding: Inference-Time Unlearning via Auxiliary Models
Cache Coherent Resampling for Efficient Test Time Scaling in LLM Reasoning via Adaptive Sequential Monte Carlo
Efficient Tail-Aware Generative Optimization via Flow Model Fine-Tuning
Teaching Molecular Dynamics to a Non-Autoregressive Ionic Transport Predictor
Learning-Augmented Online Minimization with Dual Predictions
Benchmarking Agent Memory in Interdependent Multi-Session Agentic Tasks
A robust PPG foundation model using multimodal physiological supervision
TuneAhead: Predicting Fine-tuning Performance Before Training Begins
Parallel Stochastic Gradient-Based Planning for World Models
Towards Resource-Efficient LLMs: End-to-End Energy Accounting of Distillation Pipelines
Mind the Gap: Structure-Aware Consistency in Preference Learning
The Crowded Embedding Space: A Mean-Field Mechanism for Emergent Marginalization in Retrieval-Augmented Agents
Entropy-Aware On-Policy Distillation of Language Models
AutoBaxBuilder: Bootstrapping Code Security Benchmarking
Uncertainty-Guided Exploration and Stable Planning for Sparse-Reward Manipulation from Limited Demonstrations
Learning Situated Awareness in the Real World
Removing Sandbagging in LLMs by Training with Weak Supervision
Dimensional Collapse in Transformer Attention Outputs: A Challenge for Sparse Dictionary Learning
Theoretical Investigation on Inductive Bias of Isolation Forest
Byte Pair Encoding for Efficient Time Series Forecasting
Learning to Explore: Scaling Agentic Reasoning via Exploration-Aware Policy Optimization
Beyond Tokens: Enhancing RTL Quality Estimation via Structural Graph Learning
Gauge-Equivariant Graph Networks via Self-Interference Cancellation
SpaCeFormer: Fast Proposal-Free Open-Vocabulary 3D Instance Segmentation
$A_2$DEPT: Large Language Model–Driven Automated Algorithm Design via Evolutionary Program Trees
Is One Layer Enough? Understanding Inference Dynamics in Tabular Foundation Models
Hamiltonian Asymmetric Fusion: One-Way Safe Directed Refinement under Modality Imbalance
Infinite-Dimensional Generative Diffusions via Doob’s h-Transform
Causal Matrix Completion under Multiple Treatments via Mixed Synthetic Nearest Neighbors
Beyond Model Ranking: Predictability-Aligned Evaluation for Time Series Forecasting
MemCast: Memory-Driven Time Series Forecasting with Experience-Conditioned Reasoning
Optimal Transport for LLM Reward Modeling from Noisy Feedback
Factorized Scheduling Principle: Learning Interpretable and Transferable Policies via Structured Additive Functions
Bayesian Rain Field Reconstruction using Commercial Microwave Links and Diffusion Model Priors
A Robust Optimization Guided Pruning Framework for Vision and Large Language Models
d2: Improving Reasoning in Diffusion Language Models via Trajectory Likelihood Estimation
Attend to Anything: Foundation Model for Unified Human Attention Modeling
Scaling Transformers for End-to-End Discrete Audio Tokenization
MapDream: Task-Driven Map Learning for Vision-Language Navigation
Identifiable Markov Switching Models with Instantaneous Effects and Exponential Families
SPUR: Scale-Partitioned Uncertainty Rectification for Robust UAV-on-UAV Interception
Dual Mechanisms of Value Expression: Intrinsic vs. Prompted Values in Large Language Models
Advancing SVD-based LLM Compression via Layer-Wise Error Model Search
The Unlearnability Phenomenon in RLVR for Language Models
Multi-Distribution Robust Conformal Prediction
Reasoning Can Be Restored by Correcting a Few Decision Tokens
E-VAds: An E-commerce Short Videos Understanding Benchmark for MLLMs
Model-Based Diffusion Sampling for Predictive Control in Offline Decision Making
Causal Flow Q-Learning for Robust Offline Reinforcement Learning
Leveraging Evidence Priors for Robust Prompt Learning under Noisy Supervision in Vision-Language Models
Efficient LLM Moderation with Multi-Layer Latent Prototypes
When Random Saliency Looks Trained: Architectural Center Bias in CNN Interpretability
PnP-Corrector: A Universal Correction Framework for Coupled Spatiotemporal Forecasting
CiteGuard: Conformal False-Discovery Control for Faithful Retrieval-Augmented Generation
Improving Classifier-Free Guidance of Flow Matching via Manifold Projection
PAWS: Preference Learning with Advantage-Weighted Segments
Synthesizing Multimodal Geometry Datasets from Scratch and Enabling Visual Alignment via Plotting Code
Explicit representation of germline and non-germline residues improves antibody language modeling
Saliency-Aware Model Merging
Breaking the Exploration Bottleneck: Rubric-Scaffolded Reinforcement Learning for Open-Ended LLM Reasoning
DEER: A Benchmark for Evaluating Deep Research Agents on Expert Report Generation
Reasoning Cache: Continual Improvement Over Long Horizons via Short-Horizon RL
Gradient Flow Dynamics and Implicit Bias of Diagonal Linear Networks under Infinitesimal Initialization
Reasoning Models Are Test Exploiters: Rethinking Multiple Choice
Context-Aware Reasoner: Enhancing Contextual Reasoning in Multimodal Large Language Models
Diffusion Controller: Framework, Algorithms and Parameterization
Obliviate: Efficient Unlearning in Recommender Systems
Unifying Dataset Pruning and Distillation for Efficient Large-scale Compression
Beyond Continuity: Simulation-free Reconstruction of Discrete Branching Dynamics from Single-cell Snapshots
GradPower: Powering Gradients for Faster Language Model Pre-Training
Little By Little: Continual Learning via Incremental Mixture of Rank-1 Associative Memory Experts
Probabilistic Pretraining for Improved Neural Regression
Domain Transfer Becomes Identifiable via a Single Alignment
Speculative Sampling For Faster Molecular Dynamics
Motion Attribution for Video Generation
Bridging the Knowledge-Prediction Gap in LLMs on Multiple-Choice Questions
Critique-Guided Distillation for Robust Reasoning via Refinement
UniCode: Augmenting Evaluation for Code Reasoning
QTALE: Quantization-Robust Token-Adaptive Layer Execution for LLMs
TritonGym: A Benchmark for Agentic LLM Workflows in Triton GPU Code Generation
Bilevel Optimization over Saddle Points of Zero-Sum Markov Games
$\textit{S}$-SPPO: Semantic-Calibrated Self-Play Preference Optimization
Spurious Correlation Learning in Preference Optimization: Mechanisms, Consequences, and Mitigation via Tie Training
Tri-Scale Neural ODEs for Continuous Multi-Omics Disease Modeling
Efficient Reasoning with Hidden Thinking
Uncertainty-Constrained Trustworthiness for Graph Learning
Minimizing Mismatch Risk: A Prototype-Based Routing Framework for Zero-shot LLM-generated Text Detection
How Few-Shot Examples Add Up: A Causal Decomposition of Function Vectors in In-Context Learning
TOM-SWE: User Mental Modeling For Software Engineering Agents
Improved Convergence of Score-Based Diffusion Models via Prediction-Correction
Sinkhorn Treatment Effects: A Causal Optimal Transport Measure
BIT-LLM: Brain Instruction Tuned LLM with persistent Cross-Attention for fMRI-to-Text Decoding
On the Convergence of Adaptive Gradient Methods for Nonconvex Optimization
Joint Enhancement and Classification using Coupled Diffusion Models of Signals and Logits
ATLAS: Learning to Optimally Memorize the Context at Test Time
Expert Routing with Synthetic Data for Domain Incremental Learning
FUSE: Full‑spectrum Unlearnable Examples via Spectral Equalization
UCB Exploration for Fixed-Budget Bayesian Best Arm Identification
A Theoretical Framework for Modular Learning of Robust Generative Models
Physics-Aware Spatiotemporal Causal Graph Network for Forecasting with Limited Data
TapSampling: Inference-Time Sampling with a Task-Progress-Understanding Verifier for Robotic Manipulation
Adaptive Token Refinement in Long-Tailed Large Vision-Language Models Fine-Tuning
TEAM: Temporal–Spatial Consistency Guided Expert Activation for MoE Diffusion Language Model Acceleration
The Bridge-Garden Dilemma in LLM Distillation: Why Mixing Hard and Soft Labels Works
Zero-Shot Off-Policy Learning
MARS-SQL: A Multi-Agent Reinforcement Learning Framework For Text-To-SQL
PepCompass: Navigating Peptide Embedding Spaces Using Riemannian Geometry
Can Muon Fine-tune Adam-Pretrained Models?
Conformal C2ST: Turning weak classifiers into strong two-sample tests
CodeChemist: Test-Time Scaling for Low-Resource Code Generation via Functional Knowledge Transfer
Efficient privacy loss accounting for subsampling and random allocation
PromptPilot: Game-Theoretic Multi-Agent Prompt Optimization for Segment Anything
RLIE: Rule Generation with Logistic Regression, Iterative Refinement, and Evaluation for Large Language Models
AES: Curing Optimizer Blindness in Long-Tailed Recognition via State-Aware Correction
Structured Progressive Knowledge Activation for LLM-Driven Neural Architecture Search
DynaVieW: Schema-Guided World Modeling for Understanding Hierarchical Visual Dynamics
Ultrafast On-Chip Online Learning via Spline Locality in Kolmogorov–Arnold Networks
Task-Aware Preference Calibration for Direct Preference Optimization
LogicSAGE: Neuro-Symbolic Reasoning with Socratic-Guided Enhancement
Forget by Uncertainty: Orthogonal Entropy Unlearning for Quantized Neural Networks
Beyond Description: Federated Adaptation via Semantic-Visual Prototype Alignment
SafeCompass: Dynamic Chain-of-Thought Steering via Inference-Time Safety Signals
Two Calm Ends and the Wild Middle: A Geometric Picture of Memorization in Diffusion Models
Scalable Medical Multimodal Fusion via Symmetric Consistency Modeling
SafeSpec: Fast and Safe LLM via Dynamic Reflective Sampling
Injecting Distributional Awareness into MLLMs via Reinforcement Learning for Deep Imbalanced Regression
DiscoverLLM: From Executing Intents to Discovering Them
Evaluating Bivariate Causal Statements Based on Mutual Compatibility
Aitchison Embeddings for Learning Compositional Graph Representations
ProMeCD: Unifying Long-Tailed and Noisy Label Learning via White-Box Control
MusicDET: Zero-Shot AI-Generated Music Detection
A Unified Density Operator View of Flow Control and Merging
Position: AGI Requires a Coordination Layer on Top of Pattern Repositories
DARC: Disagreement-Aware Alignment via Risk-Constrained Decoding
PolicyGuard: Towards Test-time and Step-level Adversary Defense for Reinforcement Learning Agent
WorldPlay: Towards Long-Term Geometric Consistency for Real-Time Interactive World Modeling
AMA-Bench: Evaluating Long-Horizon Memory for Agentic Applications
EchoingPixels: Aliasing-Resistant Joint Token Reduction for Audio-Visual LLMs
The Hidden Link between RLHF and Contrastive Learning
LMM4-IC4K: A Large Multimodal Model Powered Integrated Circuit Footprint Geometry Understanding
MIND: Decoupling Model-Induced Label Noise via Latent Manifold Disentanglement
Dynamics of neural scaling laws in random feature regression with powerlaw-distributed kernel eigenvalues
Desirable Effort Fairness and Optimality Trade-offs in Strategic Learning
An analytic theory of convolutional neural network inverse problems solvers
ProtocolBench: Which LLM MultiAgent Protocol to Choose?
InertialAR: Autoregressive 3D Molecule Generation with Inertial Frames
CentaurEval: Benchmarking Human-in-the-Loop Value in Agentic Coding
Bullet Trains: Parallelizing Training of Temporally Precise Spiking Neural Networks
Federated Distillation for Whole Slide Image via Gaussian-Mixture Feature Alignment and Curriculum Integration
DFSAttn: Dynamic Fine-grained Sparse Attention for Efficient Video Generation
Model-Free Robust Average-Reward Reinforcement Learning with Sample Complexity Analysis
Bridging Time and Frequency: A Joint Modeling Framework for Irregular Multivariate Time Series Forecasting
Inverting Data Transformations via Diffusion Sampling
A Theory of Contrastive Learning with Natural Images
MiniMax Learning of Interpretable Factored Stochastic Policies from Conjoint Data, with Uncertainty Quantification
Compositional Generative Modeling from Decentralized Data
SERA: Soft-Verified Efficient Repository Agents
Rank-guided Diffusion for Noise Few-Shot Learning
Quaternion Self-Attention with Shared Scores
FUSE: Quantifying Uncertainty in Vision-Language Models by Bayesian Fusing Epistemic and Aleatoric Uncertainty
GradMem: Learning to Write Context into Memory with Test-Time Gradient Descent
Persistent Backdoor Attacks in Class-Incremental Learning via Structural Invariant Anchoring
Efficient and Uncertainty-Aware Diffusion Framework for Offline-to-Online Reinforcement Learning
DREAM: A Unified Framework for Drift-Corrected Federated Multi-Objective Learning
FLARE-AI: Flaw Reporting for AI
Single-Head Attention in High Dimensions: A Theory of Generalization, Weights Spectra, and Scaling Laws
No Retraining at Edge: Efficient Resource-Aware Mixed-Precision Quantization via Federated Supernet Learning
Test-time Offline Reinforcement Learning on Goal-related Experience
Accelerated and Stable Convergence with Anchored Generalized Optimistic Method
Optimal Regularization for Performative Learning
Scalable and Interpretable Representation Alignment with Ordinal Similarity
Rethinking Visual Intelligence: Insights from Video Pretraining
Can Agents Generalize to the Open World? Unveiling the Fragility of Static Training in Tool Use
Multicalibration Yields Better Matchings
Acoustic Interference: A New Paradigm Weaponizing Acoustic Latent Semantic for Universal Jailbreak against Large Audio Language Models
SURF: Separation via Unsupervised Remixing Flow
Position: EU AI Act's Research Exemptions Can Break the Publication Norms of Major AI Conferences
RubricRobustness: Evaluating the Sensitivity of Rubrics-Based Benchmarks to Simple Perturbations
Optimal Design for Multinomial Logit Model with Applications to Best Assortment Identification
Position: Comprehensive AI governance requires addressing non-model capability gains
LightningRL: Breaking the Accuracy–Parallelism Trade-off of Block-wise dLLMs via Reinforcement Learning
TMD-Bench: A Multi-Level Evaluation Paradigm for Music–Dance Co-Generation
VideoLoom: A Video Large Language Model for Joint Spatial-Temporal Understanding
KITE: Knowledge-Guided Probabilistic Modeling for Time Series Forecasting with Exogenous Variables
Position: Reframing Hallucination: Latent Space Geodesics as a Pathway for Generative Discovery
KUMA: A Novel Framework with Koopman Separation and Efficient Multilevel Extraction in Time Series Forecasting
World-Shaper: A Unified Framework for 360° Panoramic Editing
Universal One-third Time Scaling in Learning Peaked Distributions
Reasoning about Reasoning: BAPO Bounds on Chain-of-Thought Token Complexity in LLMs
Improving LLM-Based Recommenders with Conservative Generative Flow Networks
Variable Clustering via Distributionally Robust Nodewise Regression
Reinforcement Learning via Self-Distillation
ReVSI: Rebuilding Visual Spatial Intelligence Evaluation for Accurate Assessment of VLM 3D Reasoning
Position: Interpretability in Deep Time Series Models Demands Semantic Alignment
Predicting Future Utility: Global Combinatorial Optimization for Task-Agnostic KV Cache Eviction
Mining Tensor/Neuron-Level Sparsity to Maximize Mixture-of-Experts Potential in Post-Training and Inference
Investigating Component Contributions in Multi-Agent ML Systems
Predicting evolutionary rate as a pretraining task improves genome language model representations
3D MeanFlow: One-Step Point Cloud Completion and Generation via Average-Velocity Transport
Preserve-Then-Quantize: Balancing Rank Budgets for Quantization Error Reconstruction in LLMs
OpenTSLM: Time-Series Language Models for Reasoning over Multivariate Medical Text- and Time-Series Data
Dynamic Programming for Epistemic Uncertainty in Markov Decision Processes
Decomposing the Basic Abilities of Large Language Models: Mitigating Cross-Task Interference in Multi-Task Instruct-Tuning
Evidential Reasoning Advances Interpretable Real-World Disease Screening
Image Restoration via Diffusion Models with Dynamic Resolution
Error Propagation in Dynamic Programming: From Stochastic Control to American Option Pricing
iTryOn: Mastering Interactive Video Virtual Try-On with Spatial-Semantic Guidance
NBCG: Nash-Bargained Causal Game for Long-Tailed Multi-Label NLP
Sequential Kernel-based Conditional Independence Testing via Adaptive Betting
Failure-Driven Workflow Refinement
Coupled Cluster con MoLe: Molecular Orbital Learning for Neural Wavefunctions
DenseMLLM: Standard Multimodal LLMs for Dense Prediction
Revisiting Distribution Correction Estimation for Offline Imitation Learning with Suboptimal Dataset
Position: Your VLM May Not Be Thinking with Interleaved Images
SOLAR for Offline MARL: Plateau-Triggered Potential Shaping under World-Model Uncertainty
Position: ICML Should Treat Hosted LLM APIs as Versioned Dependencies and Require Drift-Audit Artifacts
Speculative Safety Honeypot: Toward Proactive Defense Against Multi-turn Agent Attacks
LoRe: Adaptive Interaction-Evaluation Routing with Per-step Interaction Budgets for Iterative Graph Solvers
Differentially Private Continual Release with Relative Error
Quantifying and Optimizing Simplicity via Polynomial Representations
MarketSim: Simulating Stock Markets with Large-Scale Generative Agents
PRISM: Parallel Residual Iterative Sequence Model
Task-Aware Exploration via a Predictive Bisimulation Metric
Bridging Tokens and Geometry: Token-wise 3D Supervision for CAD Generation
Bimodal masked language modeling for bulk RNA-seq and DNA methylation representation learning
Omni-Diffusion: Unified Multimodal Understanding and Generation with Masked Discrete Diffusion
Parameters as Experts: Adapting Vision Models with Dynamic Parameter Routing
Correcting Visual Blur Induced by Attention Distraction to Reduce Hallucinations: Algorithm and Theory
Gromov-Wasserstein at Scale, Beyond Squared Norms
The Labyrinth and the Thread: Rethinking Regularizations in Sequential Knowledge Editing for Large Language Models
Principled SVD-based Delta Compression via Quantization Error Minimization
Tucker Attention: A generalization of approximate attention mechanisms
Reinforcement Learning for Tool-Calling Agents in Fast Healthcare Interoperability Resources (FHIR)
Influence-Disentangled Federated Training: Learning Models That Are Easy to Unlearn
FedPAT: Federated Test-Time Adaptation via Prototype Affinity Topology
Rethink the Role of Neural Decoders in Quantum Error Correction
MCCE: A Framework for Multi-LLM Collaborative Search in Discrete Spaces with Similarity-Filtered Preference Learning
Efficient, Validation-Free Intrinsic Quality Estimation for Large-Scale Face Recognition Datasets
SPLIT-VLM: Salience-Guided Partitioning towards Local Coverage for Importance-Aware Token Dropping in Vision-Language Models
Clustered Influence Functions
Position: Reliable AI Needs to Externalize Implicit Knowledge: A Human–AI Collaboration Perspective
Unified Multimodal Visual Tracking with Dual Mixture-of-Experts
Crowd4D: Scene-Aware Monocular 4D Crowd Reconstruction
Position: Responsible AI for AI companions must actively combat violence toward intimate partners
Benchmarking the Limits of In-Context Reinforcement Learning for Ad-Hoc Teamwork
Evaluating Sample Utility for Efficient Data Selection by Mimicking Model Weights
Scientific logicality enriched methodology for LLM reasoning: A practice in physics
Efficient, Property-Aligned Fan-Out Retrieval via RL-Compiled Diffusion
SliceFine: The Universal Winning-Slice Hypothesis for Pretrained Networks
Function-Valued Causal Influence in Nonlinear Time Series
Parameter-free Dynamic Regret: Time-varying Movement Costs, Delayed Feedback, and Memory
MMPD-Bench: Bridging Multimodal Fission with Multi-Polarimetric Modalities Decomposition
GAUSS: Graph-Assisted Uncertainty Quantification using Structure and Semantics for Long-Form Generation in LLMs
PyVision-RL: Forging Open Agentic Vision Models via RL
Dual-Latent Memory Routing for Vision-Language Reasoning
Position: Use Sparse Autoencoders to Discover Unknowns
HO-SFL: Hybrid-Order Split Federated Learning with Backprop-Free Clients and Dimension-Free Aggregation
Towards Streaming Synchronized Spatial Audio Generation via Autoregressive Diffusion Transformer
Low-Rank and Sparsity Are All You Need: Exploring Robust Hierarchical Latent Subspaces for Transferable Adversarial Attack
Spectral Reach: Understanding Neural Scaling as Progress into the Spectral Tail
Flow for Future: Geometric SE(3)-Equivariant Flow Matching for 3D Trajectory Prediction
Physics-Informed Distillation of Diffusion Models for PDE-Constrained Generation
Position: LLM Serving Needs Mathematical Optimization and Algorithmic Foundations, Not Just Heuristics
Local-Minima-Preserving Polynomial Relaxation of Ising Problems
UnMaskFork: Test-Time Scaling for Masked Diffusion via Deterministic Action Branching
Causal Structure Learning for Sparse Matrix Fill-in Reduction
Reinforcement Learning with Pairwise Preferences in Long-Term Decision Problems
Steer Like the LLM: Activation Steering that Mimics Prompting
Epistemic Uncertainty Quantification for Pre-trained VLMs via Riemannian Flow Matching
CorrSteer: Generation-Time LLM Steering via Correlated Sparse Autoencoder Features
MultiPriv: Benchmarking Individual-Level Privacy Reasoning in Vision-Language Models
Efficient Test-time Inference for Generative Planning Models with OCL Search
Doppler Prompting for Stable mmWave-based Human Pose Estimation
Adversarially Robust Approximate Furthest Neighbor
Unsupervised Disentanglement Without Compromises : How Functional Orthogonality Enforces Identifiability
Introspection Adapters: Training LLMs to Report Their Learned Behaviors
QEDBench: Quantifying the Alignment Gap in Automated Evaluation of University-Level Mathematical Proofs
Balancing Fidelity and Diversity in Diffusion Models via Symmetric Attention Decomposition: Hopfield Perspective
MetaStreet: Semi-Supervised Multimodal Learning for Street-Level Socioeconomic Prediction
Online Contract Design With Unknown Technology
Cross-Tactile Sensor Representation Learning
Probing How Scalable Table Data Enhances General Long-Context Reasoning
Training-Free Rate-Distortion-Perception Traversal With Diffusion
Message Passing on the Edge: Towards Scalable and Expressive GNNs
PATRA: Pattern-Aware Alignment and Balanced Reasoning for Time Series Question Answering
Zeus: Towards Tuning-Free Foundation Model for Time Series Analysis
From Prior to Pro: Efficient Skill Mastery via Distribution Contractive RL Finetuning
From Denoising to De-Channeling: Integrating Physical Channel Priors into Diffusion Models for Radio Signal Understanding
The Implicit Bias of Adam and Muon on Smooth Homogeneous Neural Networks
When Do Graph Foundation Models Transfer? A Data-Centric Theory
Interpretable Self-Supervised Learning via Representer Landmarks and Nyström Approximation
Autoregressive Direct Preference Optimization
FG-CLIP 2: A Bilingual Fine-grained Vision-Language Alignment Model
Generative Visual Code Mobile World Models
Interactive Person Retrieval via Multi-Turn Multimodal Conversation
Positive Distribution Shift as a Framework for Understanding Tractable Learning
ViEEG: Hierarchical Visual Neural Representation for EEG Brain Decoding
Graph-Preference Learning: Debiasing Network-Sampled Human Feedback for Target Welfare Estimation
SAD-Flower: Flow Matching for Safe, Admissible, and Dynamically Consistent Planning
Generalized Linear Bandits with Memory
Commit to the Bit: Reactive Reinforcement Learning Done Right
Plan for Speed: Dilated Scheduling for Masked Diffusion Language Models
$\phi$-Balancing for Mixture-of-Experts Training
Symbiosis-Inspired Knowledge Distillation for Incremental Object Detection
HypCL: Adapting CLIP in Hyperbolic Space for Continual Learning
RAIGen: Rare Attribute Identification in Text-to-Image Generative Models
ASRU: Activation Steering Meets Reinforcement Unlearning for Multimodal Large Language Models
Active Budget Allocation for Efficient Scaling Law Estimation via Surrogate-Guided Pruning
Self-CriTeach: LLM Self-Teaching and Self-Critiquing for Improving Robotic Planning via Automated Domain Generation
Fixed Budget is No Harder Than Fixed Confidence in Best-Arm Identification up to Logarithmic Factors
DEGAP: Dynamic Entropy-Guided Attention Perturbation for Contrastive Decoding in Large Vision-Language Models
CREDIT: Certified Ownership Verification of Deep Neural Networks Against Model Extraction Attacks
FAIL: Flow Matching Adversarial Imitation Learning for Image Generation
Revealing Long-context Potential of Attention Heads via Frequency Kernels
Semantic-level Backdoor Attack against Text-to-Image Diffusion Models
Language Bias in LVLMs: From In-Depth Analysis to Simple and Effective Mitigation
Global Policy-Space Response Oracles for Two-Player Zero-Sum Games
PISA: Privacy-Preserving Split Adaptation with Model IP Protection
Least-Loaded Expert Parallelism: Load Balancing An Imbalanced Mixture-of-Experts
Capacity-Aware Mixture Law Enables Efficient LLM Data Optimization
On the Accuracy of Newton Step and Influence Function Data Attributions
Tensor Train Diffusion: Leveraging Low-Rank Structures for High-Dimensional Score-Based Sampling
Adaptive Batch Sizes Using Non-Euclidean Gradient Noise Scales for Stochastic Sign and Spectral Descent
Trajectory Seriation via Spectral Tangent Alignment and Global Embedding
DiP-G: Discrete Prompting for Graph Neural Networks
PuzzleMoE: Efficient Compression of Large Mixture-of-Experts Models via Sparse Expert Merging and Bit-packed inference
The Loss Is Not Enough: Sampling Conditions and Inductive Bias in Contrastive Representation Learning
OBCache: Optimal Brain KV Cache Pruning for Efficient Long-Context LLM Inference
Multi-task Linear Regression without Eigenvalue Lower Bounds: Adaptivity, Robustness, and Safety
SimpleGPT: Improving GPT via A Simple Normalization Strategy
Score Based Error Correcting Code Decoder
Delving into Muon and Beyond: Deep Analysis and Extensions
Gradient-Based Causal Tree Ensembles: A Backbone Architecture for Heterogeneous Treatment Effects
SLQ: Bridging Modalities via Shared Latent Queries for Retrieval with Frozen MLLMs
Can Microcanonical Langevin Dynamics Leverage Mini-Batch Gradient Noise?
SCHUR-A*: Layer-wise Optimal Expert Pruning for MoEs via Schur-Complement Guided A* Search
Better, Faster: Harnessing Self-Improvement in Large Reasoning Models
Improved Convergence Analysis of Topology Dependence in Decentralized SGD
Move-Then-Operate: Behavioral Phasing for Human-Like Robotic Manipulation
Variational inference via Gaussian interacting particles in the Bures-Wasserstein geometry
X-EviProbe: Post-hoc Parameter-Free Evidential Uncertainty Quantification for Frozen Graph Neural Networks
Agent Primitives: Reuseable Latent Building Blocks for Multi-Agent Systems
Safety Alignment of LMs via Non-cooperative Games
CARE: Class-Adaptive Expert Consensus for Reliable Learning with Long-Tailed Noisy Labels
Geometry of Reason: Spectral Signatures of Valid Mathematical Reasoning
Demystifying Multimodal Biomolecular Co-design With Intrinsic Geodesic Coupling
Rethinking Sparse Mixture of Experts from a Unified Perspective
Diffract: Spectral View of LLM Domain Adaptation
AlphaRouter: Token-level Routing Between SLM and LLM with Reinforcement Learning and Tree Search
ABSINT-AI: Agentic Heap Abstractions for Abstract Interpretation
Ellipsoidal Time Series Forecasting
Adaptive Generation of Bias-Eliciting Questions for LLMs
Demystifying Scientific Problem-Solving in LLMs by Probing Knowledge and Reasoning
Statistically Undetectable Backdoors in Deep Neural Networks
Data- and Variance-dependent Regret Bounds for Online Tabular MDPs
Beyond Euclidean Clipping: Overcoming Exploration Collapse in LLM RL via Riemannian Isometric Policy Optimization
Beyond Reactivity: Proactive Adaptive Conformal Inference for Online LLM Factuality
Seeking Commonality, Preserving Specificity: A Spectral-Aware Hierarchical Framework for Cross-City Road Representation Learning
MacroGuide: Topological Guidance for Macrocycle Generation
Quartet II: Accurate LLM Pre-Training in NVFP4 by Improved Unbiased Gradient Estimation
S2GS: Streaming Semantic Gaussian Splatting for Online Scene Understanding and Reconstruction
Covariance Volume Maximization for Embodied Latent Exploration in Deep Reinforcement Learning
Advancing LLM Reasoning with Natural Language and Numerical Feedback
DirectEdit: Step-Level Accurate Inversion for Flow-Based Image Editing
VeriSimpl: Robust Optimization Modeling from Natural Language using Simplification-based Verification
ActiveUltraFeedback: Efficient Preference Data Generation using Active Learning
Eigenvectors of Experts are Training-free Non-collapsing Routers
InfVSR: Toward Consistency-Driven Streaming Generative Video Super-Resolution
Correcting Overparameterization Effects in Fair Empirical Risk Minimization
Efficient Distributed MLLM Training with Cornstarch
Decision Tree Learning on Product Spaces
Gradient Descent with Large Step Size Restores Symmetry in Deep Linear Networks with Multi-Pathway
FormalJudge: A Neuro-Symbolic Paradigm for Agentic Oversight
Accuracy-First Rényi Differential Privacy and Post-Processing Immunity
Beyond Fixed Biases: Decoding the Role of Reasoning Uncertainty in MLLM Modality Conflicts
Learnable Kernel Density Estimation for Graphs and Its Application to Graph-Level Anomaly Detection
SkillNet: Hierarchical Skill Modeling for Compositional Generalization in Vision-Language Action Models
Tighter Regret Lower Bound for Gaussian Process Bandits with Squared Exponential Kernel in Hypersphere
Sampling from Your Language Model One Byte at a Time
InfoGeo: Information-Theoretic Object-Centric Learning for Cross-View Generalizable UAV Geo-Localization
Pretrained Vision-Language-Action Models are Surprisingly Resistant to Forgetting in Continual Learning
Scalable and General Whole-Body Control for Cross-Humanoid Locomotion
Solving Imperfect-Recall Games via Sum-of-Squares Optimization
Multi-Objective Protein Design via Memory-Aware Test-Time Scaling in Diffusion Models
Inverse Depth Scaling From Most Layers Being Similar
On the Power of Source Screening for Learning Shared Feature Extractors
Selective Deferred Routing: Enabling Cost-Efficient Collaboration between Local SLMs and Remote LLMs
Multiple Choice Learning of Low-Rank Adapters for Language Modeling
Multiview Self-Representation Learning across Heterogeneous Views
FasterVAR: Plug-and-Play Acceleration for Visual Autoregressive Models
Optimal Transport with Symmetry Groups
UniMapping: Unified SLAM Framework for Map-Centric Embodied Perception
LORD-GoF: A Robust Online Detection Approach for LLM Watermarks in Sparse and Mixed Streams
How Can Mamba Learn In Context with Outliers and Generalize Provably?
CCLRec: Consensus-driven Contrastive Learning for LLM-enhanced Graph Recommendation
Kernel-based Maximum-of-difference Test for Two-sample Comparison
Embodied-DETR: End-to-End Temporal 3D Object Detection in Egocentric Views
HPS: Hyperspherical Parameter Sharing for Efficient Multi-Agent Reinforcement Learning
Dr. Kernel: Reinforcement Learning Done Right for Triton Kernel Generations
MetaDNS: Enhancing Exploration in Discrete Neural Samplers via Metadynamics
The Information Geometry of Softmax: Probing and Steering
Policy Search via Bayesian Optimization with Temporal Difference Gaussian Processes
Variational Adapter for Cross-modal Similarity Representation
Hermite-NGP: Gradient-Augmented Hash Encoding for Learning PDEs
CausalGame: Benchmarking Causal Thinking of LLM Agents in Games
Conditional Distributional Treatment Effects: Doubly Robust Estimation and Testing
Vision Language Models Cannot Reason About Physical Transformation
ReViT: Rotational-equivariant Vision Transformers for Neural PDE Solvers
Dirichlet-Prior Shaping: Guiding Expert Specialization in Upcycled MoEs
Shapley Regularized Neural Granger Causality
From Holo Pockets to Electron Density: GPT-style Drug Design with Density
CAOS: Conformal Aggregation of One-Shot Predictors
Learning Compressed Shape-Aware Molecular Representations for Virtual Screening
Learning Interpretable Options by Identifying Reward Diffusion Bottlenecks in Reinforcement Learning
Fine-grained Analysis of Brain-LLM Alignment through Input Attribution
Transporting Task Vectors across Different Architectures without Training
RiboSphere: Learning Unified and Efficient Representations of RNA Structures
Token Sparse Attention: Efficient Long-Context Inference with Interleaved Token Selection
Learnability-Driven Knowledge Assimilation for Class-Incremental Semantic Segmentation
Epistemic Gain, Aleatoric Cost: Uncertainty Decomposition in Multi-Agent Debate for Math Reasoning
OSM+: Billion-Level Open Street Map Dataset for City-wide Experiments
A Fine-Grained Understanding of Uniform Convergence for Halfspaces
PETS: A Principled Framework Towards Optimal Trajectory Allocation for Efficient Test-Time Self-Consistency
On Revisiting Entropy for Identifying Mislabeled Images
Membership Inference Attacks for Unseen Classes
Induction Heads Interpolate N-Grams
Content-Style Identification via Differential Independence
Data-Source Adaptive Online Learning under Heteroscedastic Noise
MINT: Minimal Information Neuro-Symbolic Tree for Objective-Driven Knowledge-Gap Reasoning and Active Elicitation
(1D) Ordered Tokens Enable Efficient Test-Time Search
Unfolded Laplacian Spectral Embedding: A Theoretically Grounded Approach to Dynamic Network Representation
MODUS: Decoder-only Any-to-Any Modeling of Diverse Modalities
Bridging Structure and Semantics: Uncertainty-Modulated Dual-Path Diffusion for Robust Text-Attributed Graph Learning
A Spiking Heterogeneous Harmonic Resonate-and-Fire State Space Model for Time Series
Local Minima in Quadratic-Penalty Relaxations of Binary Linear Programs
Bias in Zeroth-Order Normal Estimation for Decision-Based Attacks
ROAMM: A Benchmark Dataset for Multimodal Human Attention Decoding and EEG-to-Text Modeling During Naturalistic Reading
Towards Multimodal Large Language Models with Both Training and Inference Efficiency
IRIS: Implicit Reward-Guided Internal Sifting for Mitigating Multimodal Hallucination
Inference-time optimization for experiment-grounded protein ensemble generation
Robust Bayesian Optimisation with Unbounded Corruptions
Solving Positive Linear Programs with Differential Privacy
Diffusion Flow Matching: Dimension-Improved KL Bounds and Wasserstein Guarantees
From 2D Grids to 1D Tokens: Reforming Shared Representations for Multimodal Image Fusion
LIFT: A Novel Framework for Enhancing Long-Context Understanding of LLMs via Long Input Fine-Tuning
UFO: Chain-of-Evaluation for Omni-Condition Alignment in Multi-Modal Image Generation
Tabero: Learning Gentle Manipulation with Closed-Loop Force Feedback from Vision, Touch, and Language
MetaphorVU: Towards Metaphorical Video Understanding
Tackling Length Inflation Without Trade-offs: Group Relative Reward Rescaling for Reinforcement Learning
AutoMS: Multi-Agent Evolutionary Search for Cross-Physics Inverse Microstructure Design
Generative Large Neighborhood Search: Scalable Set Cover Optimization via Discrete Diffusion
Rays as Pixels: Learning A Joint Distribution of Video and Camera Trajectories
EmBrace: A Collective Knowledge Fusion Framework Toward Unified EEG Foundation Models
Beyond Problem Solving: UOJ-Bench for Evaluating Code Generation, Hacking, and Repair in Competitive Programming
Safety Anchor: Defending Harmful Fine-tuning via Geometric Bottlenecks
Weight Decay Improves Language Model Plasticity
3DPoV: Improving 3D understanding via Patch Ordering on Videos
When Generalized Zero-Shot Learning Meets PU Learning: A Plug-and-Play Framework for Seen-Class Bias Mitigation
What if Tomorrow is the World Cup Final? Counterfactual Time Series Forecasting with Textual Conditions
Op-CAD: Benchmarking and Investigating Operation-oriented CAD Generation
Clipped Q-Learning: Your Value Clipping Is Secretly A Robust Operator
Interactive Segmentation with Elaborate Focus Prior
SPEED: Sharpened-Teacher Distillation for Parallel Decoding of Diffusion Language Models
Local Intrinsic Dimension of Representations Predicts Alignment and Generalization in AI Models and Human Brain
Inference from Quantized Data via Normal Variance-Mean Mixtures
Game-Theoretic Co-Evolution for LLM-Based Heuristic Discovery
MedREK: Retrieval-Based Editing for Medical LLMs with Key-Aware Prompts
CLEAR: Context-Aware Learning with End-to-End Mask-Free Inference for Adaptive Subtitle Removal
The Expert Strikes Back: Interpreting Mixture-of-Experts Language Models at Expert Level
Frequency-Aware Perceptual Optimization for Low-Complexity Implicit Image Compression
Adaptive Time Series Reasoning via Segment Selection
Continual Learning With Participation Privacy: An Auditable Buffering-Aggregation Recipe
A Deep Learning Model of Mental Rotation Informed by Interactive VR Experiments
Threshold-Guided Optimization for Visual Generative Models
A Sketch-and-Project Analysis of Subsampled Natural Gradient Algorithms
Why Linear Recurrent Memory Works in Partially Observable Reinforcement Learning
CADFit: Precise Mesh-to-CAD Program Generation with Hybrid Optimization
Steering Large Language Models through the DMTA Cycle: Structure-Based Drug Design via Knowledge-Driven Bi-Level Thompson Sampling
HieRD: Hierarchical Relational Distillation for Vision-Language Embedding Models
ToMAP: Training Opponent-Aware LLM Persuaders with Theory of Mind
Agentic Confidence Calibration
D-Judge: Disrupting Multi-Turn Jailbreaks using Semantics-Preserving Output Rewriting
HilbertA: Hilbert-Curve–Aligned Sparse Attention for 2D Structured Data
Caracal: Causal Architecture via Spectral Mixing
Harmonized Dual Policy Improvement for Modelic Reinforcement Learning
Active Regression for Single-Index Models with Unknown Link Functions
VectorWorld: Efficient Streaming World Model via Diffusion Flow on Vector Graphs
Cello: A Universal Cell-wise Feature Aggregation framework for Reliable Pathology Images Analysis
CoD-Lite: Real-Time Diffusion-Based Generative Image Compression
Identifying Connectivity Distributions from Neural Dynamics Using Flows
Error-Driven Graph Augmentation for Mesh-Based PDE Surrogates
MV-FGAD: Towards Efficient and Effective Federated Graph Anomaly Detection via Multi-view Learning
RT-Lynx: Putting the GEMM Sparsity In a Right Way for Diffusion Models
Expert-guided Clinical Text Augmentation via Query-Based Model Collaboration
Towards Achieving Optimal Strong Regret and Constraint Violation via Computationally Efficient Model-free RL
HERMES: Towards Efficient and Verifiable Mathematical Reasoning in LLMs
Must All Negatives Be Pushed Away Equally? Uncertainty-Aware Cross-View Geo-Localization via Normal Inverse Gamma Distribution
LAMP: Data-Efficient Linear Affine Weight-Space Models for Parameter-Controlled 3D Shape Generation and Extrapolation
Graph Alignment via Dual-Pass Spectral Encoding and Latent Space Communication
4RC: 4D Reconstruction via Conditional Querying Anytime and Anywhere
DocOS: Towards Proactive Document-Guided Actions in GUI Agents
TerraBind: Fast and Accurate Binding Affinity Prediction through Coarse Structural Representations
WEVSR: Video Diffusion Generators for Real-World Video Super‑Resolution with Wavelet-Enhanced VAE Encoder
Over-Alignment vs Over-Fitting: The Role of Feature Learning Strength in Generalization
VideoKR: Towards Knowledge- and Reasoning-Intensive Video Understanding
Efficient Public Verification of Private ML via Regularization
Unifying Heterogeneous Multi-Modal Remote Sensing Detection Via Language-Pivoted Pretraining
Statistical Consistency and Generalization of Contrastive Representation Learning
GPan-LoRA: Gaussian Process Amortized Networks for Bayesian Low-Rank Adaptation in Large Language Models
gp2Scale: A Class of Compactly Supported Non-Stationary Kernels and Distributed Computing for Exact Gaussian Processes on 10 Million Data Points
Graph-GRPO: Training Graph Flow Models with Reinforcement Learning
General Quantification of Covariate and Concept Shifts
Geometry-Correct Diffusion Posterior Sampling with Denoiser-Pullback Curvature Guidance and Manifold-Aligned Damping
Dive into the Scene: Breaking the Perceptual Bottleneck in Vision-Language Decision Making via Focus Plan Generation
Learning Structured Reasoning via Tractable Trajectory Control
Bridging Dynamics and Data: A Unified Diffusion Framework for Mechanistically-Informed Epidemic Forecasting
Think Twice Before You Act: Enhancing Agent Behavioral Safety with Thought Correction
iVGR: Internalizing Visually Grounded Reasoning for MLLMs with Reinforcement Learning
Forget to Know, Remember to Use: Context-Aware Unlearning for Large Language Models
The Easy, the Hard, and the Learnable: Confidence and Difficulty-Adaptive Policy Optimization for LLM Reasoning
Respecting Modality Gap in Post-hoc Out-of-distribution Detection with Pre-trained Vision-Language Models
When Shared Knowledge Hurts: Spectral Over-Accumulation in Model Merging
PointCHR: Point Cloud Analysis via Curvature-Aware Hyperbolic Rectification
Not All Answers Are Contextually Persuadable: Inference Dynamics in Large Language Models under Contextual Influence
TexEditor: Structure-Preserving Text-Driven Texture Editing
Who Evaluates AI's Social Impacts? Mapping Coverage and Gaps in First and Third Party Evaluations
Demystifying LLM-as-a-Judge: Analytically Tractable Model for Inference-Time Scaling
Explaining Concept Shift with Interpretable Feature Attribution
Set Diffusion: Interpolating Token Orderings between Autoregression and Diffusion for Fast and Flexible Decoding
Depth over Fidelity in Fixed-Budget Noisy Evolution Strategies
EARL: Towards a Unified Analysis-Guided Reinforcement Learning Framework for Egocentric Interaction Reasoning and Pixel Grounding
GeoDM: Geometry-aware Distribution Matching for Dataset Distillation
Weight-Space Learning for Certifiable Few-shot Transfer Learning
Small Agent Group is the Future of Digital Health
EgoTactile: Learning Grasp Pressure for Everyday Objects from Egocentric Video
Assistive Prompt Mediation: Evaluating Language Models Under Accessibility Constraints
When Do Diffusion Models Learn to Generate Multiple Objects?
Message Tuning Outshines Graph Prompt Tuning: A Prismatic Space Perspective
From Zero to Hero: Advancing Zero-Shot Foundation Models for Tabular Outlier Detection
Reflect-then-Correct: Rebalancing Task Optimization for Generalizable Meta-Reinforcement Learning via Distributional Value Error Reduction
ProOPF: Benchmarking and Improving LLMs for Professional-Grade Power Systems Optimization Modeling
Deep Pre-Alignment for VLMs
Multi-Objective Preference Optimization: Improving Human Alignment of Generative Models
VDW-GNNs: Vector diffusion wavelets for geometric graph neural networks
What If We Allocate Test-Time Compute Adaptively?
LAGEA: Language Guided Embodied Agents for Robotic Manipulation
Formal Concept Lattices are Good Semantic Scaffolds for Concept-Based Learning
XRPO: Pushing the Limits of GRPO with Targeted Exploration and Exploitation
Any-dimensional invariant universality
On the Infinite Width and Depth Limits of Predictive Coding Networks
Adaptive Personalized Federated Learning via Multi-task Averaging of Kernel Mean Embeddings
Beyond Sample-Level Forgetting: Improving Reliability in Multimodal Unlearning
IdEst: Assessing Self-Supervised Learning Representations via Intrinsic Dimension
A Theoretical Framework for Statistical Evaluability of Generative Models
$L^3$: Large Lookup Layers
Does Reinforcement Fine-Tuning Improve Generalization of LLM Agents? An Empirical Study
Glimpse: Geometry Learning of Multi-scale Structural Priors for 3D Pose Estimation
CHB: A Diagnostic Toolkit for Hardness-Aware Clustering Evaluation
QiMeng-ChipV-RTL: Exploiting Information Locality for IP-level Verilog Generation
BIOARC: Discovering Optimal Neural Architectures for Biological Foundation Models
Magnitude Distance: A Geometric Measure of Dataset Similarity
DualTimesField: Rethinking Time Series as Continuous-Time Trends and Events
L-SR1: Learned Symmetric-Rank-One Preconditioning
On Contraction of Sequential and Offset Rademacher Complexities
FlowState: Sampling-Rate‑Equivariant Time‑Series Forecasting
Understanding Dynamic Compute Allocation in Recurrent Transformers
Norm$\times$Direction: Restoring the Missing Query Norm in Vision Linear Attention
Any3D-VLA: Enhancing VLA Robustness via Diverse Point Clouds
ToaSt: Token Channel Selection and Structured Pruning for Efficient ViT
TIC-VLA: A Think-in-Control Vision-Language-Action Model for Robot Navigation in Dynamic Environments
MM-Spectrum: Multimodal Multi-spectral Molecular Structural Elucidation with a Stable MoE Framework
Coverage ≠ Exposure: Auditable Control of Same-Support Tail Failures under Multimodal Missingness
Training-Free Guided Diffusion for Planning: A Unified Framework via Doob’s h-Transform with Safety Guarantees
Detached Skip-Links and $R$-Probe: Decoupling Feature Aggregation from Gradient Propagation for MLLM OCR
ITSPACE: Monotone Gaussian Optimal Transport Updates
When Planning Fails Despite Correct Execution: On Epistemic Calibration for LLM-Based Multi-Agent Systems
Representational Similarity and Model Behavior in Multi-Agent Interaction
OSAQ: Outlier Self-Absorption for Accurate Low-bit LLM Quantization
DroneDINO: Towards Heterogeneous Routed Mixture of Experts for Drone-based Unified Object Detection
Rethinking Parameter Sharing as Graph Coloring for Structured Compression
Factored Classifier-Free Guidance
LDARNet: DNA Adaptive Representation Network with Learnable Tokenization for Genomic Modeling
View Space: Learning Representation across Arbitrary Graphs
Rethinking Feature Alignment in Generalist Graph Anomaly Detection: A Relational Fingerprint-based Approach
Structure-Aware Riemannian Flow Matching for Registration and Fusion of Hyperspectral and Multispectral Images
Adaptive Protein Tokenization
Hierarchical Procedural Meta-Reasoning for Generalizable Multimodal Agents
MuonSSM: Orthogonalizing State Space Models for Sequence Modeling
Physiology as Language: Translating Respiration to EEG during Sleep
SORA: Free Second-Order Attacks in Fast Adversarial Training
TokSuite: Measuring the Impact of Tokenizer Choice on Language Model Behavior
Robust and Consistent Ski Rental with Distributional Advice
Adversarial Training for Process Reward Models
Normalizing Flows with Iterative Denoising
Kalman Linear Attention: Parallel Bayesian Filtering For Efficient Language Modeling and State Tracking
CoPE: A Framework for Optimizing Coordination between Planning and Execution in LLM-based Agents
Discrete Tilt Matching
Parameter Decorrelation via Transition-Variance Alignment for Multivariate Time-series Forecasting
Toward Structural Multimodal Representations: Specialization, Selection, and Sparsification via Mixture-of-Experts
ECG-R1: Protocol-Guided and Modality-Agnostic MLLM for Reliable ECG Interpretation
A Cartesian-3j Framework for Machine Learning Interatomic Potentials
Generalizing Stochastic Smoothing for Differentiation and Gradient Estimation
GAM-RAG: Gain-Adaptive Memory for Evolving Retrieval in Retrieval-Augmented Generation
Shuffle the Context: RoPE-Perturbed Self-Distillation for Long-Context Adaptation
GENEB: Why Genomic Models Are Hard to Compare
Learning Flexible Generalization in Video Quality Assessment by Bringing Device and Viewing Condition Distributions
Search for Truth from Reasoning: A Dynamic Representation Editing Framework for Steering LLM Trajectories
FedFit: Federated Dynamic Sparse Training via Fisher Information scoring
From Individual Calibration to Reliable Classifiers: ALD Parameterization with mPAIC Guarantees
Esoteric Language Models: A Family of Any-Order Diffusion LLMs
Correspondence Cognitive Learning for Multi-Modal Object Re-Identification
Spherical Steering: Geometry-Aware Activation Rotation for Language Models
Why DDIM Hallucinates More Than DDPM: A Theoretical Analysis of Reverse Dynamics
Bounded Hyperbolic Tangent: A Stable and Efficient Alternative to Pre-Layer Normalization in Large Language Models
ScaleEnv: Scaling Environment Synthesis from Scratch for Generalist Interactive Tool-Use Agent Training
Maximin Relative Improvement: Fair Learning as a Bargaining Problem
Stability-Aware Feature Design for Robust Watermark Detection in Machine-Generated Text
Predictable Compression Failures: Order Sensitivity and Information Budgeting for Evidence-Grounded Binary Adjudication
Native Parallel Reasoner: Reasoning in Parallelism via Self-Distilled Reinforcement Learning
Contextualized Visual Personalization in Vision-Language Models
AI Cartography: Mapping the Latent Landscape of AI Benchmark Ecosystems
DecodeShare: Tracing the Shared Pathways of LLM Decode-Time Decisions
MGAL: A Multilingual Granularity-Aware Long-Context Benchmark
Beyond Temperature: Hyperfitting as a Late-Stage Geometric Expansion
Rotary Position Encodings for Graphs
Beyond Drift: Stabilizing Subjective LLM Evaluation with Information-Theoretic Rubrics
Training-Free Multimodal Large Language Model Orchestration
Certificate-Guided Pruning for Stochastic Lipschitz Optimization
EduMirror: Modeling Educational Social Dynamics with Value-driven Multi-agent Simulation
Select to Think: Unlocking SLM Potential with Local Sufficiency
MiVE: Multiscale Vision-language features for reference-guided video Editing
Scaling depth capacity via zero/one-layer model expansion
The Art of Interrogation: Consistency Amplifies Factuality in Spatial Reasoning
Geometric Reciprocity: Unlocking Self-Supervision for Stereoscopic Video Generation
Statistically Calibrated Scaling for Token Merging in Transformers
Mixtures Closest To A Given Measure: A Semidefinite Programming Approach
Stability Analysis of Sharpness-Aware Minimization
Autoregressive Language Models are Secretly Energy-Based Models: Insights into the Lookahead Capabilities of Next-Token Prediction
CLIMB: Taming the LoRA Residency Cliff in Multi-LoRA Serving
Unlearning in Diffusion Models: A Unified Framework with KL Divergence and Likelihood Constraints
A Conflict-aware Evidential Framework for Reliable Sleep Stage Classification
RADIO1D: Elastic Representations for Condensed Vision Modeling
SafeSearch: Automated Red-Teaming of LLM-Based Search Agents
How Out-of-Distribution Detection Learning Theory Enhances Transformer: Learnability and Reliability
Variational Inference for Uncertain Optimal Transport via Sinkhorn Parametrization
AG-REPA: Causal Layer Selection for Representation Alignment in Audio Flow Matching
MSP: Probabilistically Consistent Multi-Scale Action Generation
MLLM-4D: Towards Visual-based Spatial-Temporal Intelligence
Anti-Backdoor Coreset Selection via Cumulative Entropy
Sparse Topology-Aware Pairwise Scoring for Large-Scale Multi-Agent Reinforcement Learning
Beyond External Monitors: Enhancing Transparency of Large Language Models for Easier Monitoring
Class-Prior Perturbation-Robust Regularization for Imbalanced Unreliable Partial Label Learning
DIVE: Scaling Diversity in Agentic Task Synthesis for Generalizable Tool Use
LLMs Lean on Priors, Not Programming Language Semantics
Forward-Chaining Temporal Point Process
Latent Laplace Diffusion for Irregular Multivariate Time Series
LearniBridge: Learnable Calibration of Feature Caching for Diffusion Models Acceleration
When Actions Go Off-Task: Detecting and Correcting Misaligned Actions in Computer-Use Agents
TabPack: Efficient Hyperparameter Ensembles for Tabular Deep Learning
Olmix: A Framework for Data Mixing Throughout LM Development
Security–Fidelity Tradeoffs: No Universal Defense Against Prompt Injection
Towards a Unified Generative Model for Scarce Time Series with Domain Experts
EGG: An Expert-Guided Agent Framework for Kernel Generation
Predicting the Emergence of Induction Heads in Language Model Pretraining
Q-Tab: Quantized Tabular Data Generator
Conditional KRR: Injecting Unpenalized Features into Kernel Methods with Applications to Kernel Thresholding
Automatic Layer Selection for Hallucination Detection
Evaluating LLM Uncertainty in Long-Form Generation Using Deterministic Ground Truth
SlerpFlow: Spherical Trajectory Correction for Rectified Flow Inversion
A Strictly Proper Scoring Rule and a Calibration Metric for Interval-Censored Data Analysis
cMoLLM at Scale: Horizontal Scaling Laws for Convolutionally-Gated Mixture-of-LLMs
Retrieval-Aware Distillation for Transformer-SSM Hybrids
Directly Optimizing Natural Language Explanations for Behavioral Faithfulness: Simulatability and Recoverability
WaveSSM: Multiscale State-Space Models for Non-stationary Signal Attention
Bootstrapped Exploration with Causal Reasoning: A Training Paradigm for Adaptive Forecasting Agent
BizFinBench.v2: Towards Reliable LLMs in Finance via Real-User Data and Offline/Online Bilingual Evaluation
Gradient Flow Through Diagram Expansions: Learning Regimes and Explicit Solutions
PACEAttention: Principled and Adaptive Feature Compression-Expansion Grounded in the Geometry of $\text{MCR}^2$
The Quality-Utility Paradox: Why High-Reward Data Impairs Small Model Mathematical Reasoning
A Systematic Study of Behavioral Cloning for Scientific Data Annotation
Scaling Agentic Verifier for Competitive Coding
Unraveling Syntax: Language Modeling and the Substructure of Grammars
Can Recommender Systems Teach Themselves? A Recursive Self-Improving Framework with Fidelity Control
Efficient Mismatch-Tolerant Coding for Model-Driven Compression
Topology-Preserving Neural Operator Learning via Hodge Decomposition
TMS: Trajectory-Mixed Supervision for On-Policy Self Distillation
ArcVQ-VAE: A Spherical Vector Quantization Framework with ArcCosine Additive Margin
Expert-level Leaf Cell Layout Generation via Preference-Optimized LLM
Pareto-Guided Optimal Transport for Multi-Reward Alignment
A Unifying View of Variational Generative Wasserstein Flows
A Regime-Aware Trajectory Prediction Framework for 1000+ Systems Biology Models
Layer-wise Gradient Disentanglement: Decoupling Semantics and Preferences in Direct Preference Optimization
Stem: Rethinking Causal Information Flow in Sparse Attention
Auto-regressive In-context Demonstration Selection
Any-Order GPT as Masked Diffusion Model: Decoupling Formulation and Architecture
BLOCK-EM: Preventing Emergent Misalignment via Latent Blocking
Demystifying Action Space Design for Robotic Manipulation Policies
Skill Neologisms: Towards Skill-based Continual Learning
Batched Contextual Reinforcement
Re-FORC: Adaptive Reward Prediction for Efficient Chain-of-Thought Reasoning
ASAP: Exploiting the Satisficing Generalization Edge in Neural Combinatorial Optimization
HSGG: Training-Free Hierarchical Scene Graph Generation with Geometry-Guided Relation Reasoning
BioProBench: A Corpus and Benchmark for Biological Protocol Reasoning in Autonomous Science
SPATIA: Multimodal Generation and Prediction of Spatial Cell Phenotypes
WIND: Weather Inverse Diffusion for Zero-Shot Atmospheric Modeling
The Surprising Difficulty of Search in Model-Based Reinforcement Learning
Improved Algorithms for Nash Welfare in Linear Bandits
Gradient Preconditioning for Efficient and Reliable Reward-Guided Generation
PluRel: Synthetic Data unlocks Scaling Laws for Relational Foundation Models
Generative Online Reinforcement Learning
Eyes-on-Me: Scalable RAG Poisoning through Transferable Attention-Steering Attractors
Just Ask: Curious Code Agents Reveal System Prompts in Frontier LLMs
Coevolutionary Continuous Discrete Diffusion: Make Your Diffusion Language Model a Latent Reasoner
Courtroom Analogy: New Perspective on Uncertainty-Aware Classification
AutoRAS: Learning Robust Agentic Systems with Primitive Representations
ProbMoE: Differentiable Probabilistic Routing for Mixture-of-Experts
Plan, Decouple, Assimilate: Physics-Aware Object Insertion in Remote Sensing Imagery
Transform Trained Transformer for Accelerating Native 4K Video Generation
Cooperative Variance Estimation and Bayesian Neural Networks for Disentangling Aleatoric and Epistemic Uncertainties
Variational Speculative Decoding: Rethinking Draft Training from Token Likelihood to Sequence Acceptance
Parametric Prior Mapping Framework for Non-stationary Probabilistic Time Series Forecasting
MergeMix: Optimizing Mid-Training Data Mixtures via Learnable Model Merging
Elign: Equivariant Diffusion Model Alignment from Foundational Machine Learned Force Fields
Energy-based Compositional Diffusion Planning
ChartE$^{3}$: A Comprehensive Benchmark for End-to-End Chart Editing
PHALAR: Phasors for Learned Musical Audio Representations
AdaSplash-2: Faster Differentiable Sparse Attention
Scaling-Aware Adapter for Structure-Grounded LLM Reasoning
Reading the Cell, Designing the Cure: Perturbation-Conditioned Molecular Diffusion for Function-Oriented Drug Design
Measuring Intent Comprehension in LLMs
Local Covariate Selection for Average Causal Effect Estimation without Pretreatment and Causal Sufficiency Assumptions
An Algebraic View of the Expressivity of Recurrent Language Models
Agent Learning via Early Experience
MedMamba: Multi-View State Space Models with Adaptive Graph Learning for Medical Time Series Classification
h1: Bootstrapping LLMs to Reason over Longer Horizons via Reinforcement Learning
Beyond Scalars: Evaluating and Understanding LLM Reasoning via Geometric Progress and Stability
On the Sample Efficiency of Inverse Dynamics Models for Semi-Supervised Imitation Learning
DiffStyle3D: Consistent 3D Gaussian Stylization via Attention Optimization
IVQA-LD: Inclusive Multimodal Understanding for Population with Limb Deficiency
Can Large Language Models Generalize Procedures Across Representations?
Single-Rollout Hidden-State Dynamics for Training-Free RLVR Data Selection
From Statics to Dynamics: Physics-Aware Image Editing with Latent Transition Priors
Regret Pre-training: Bridging Prior and Posterior Views for Enhanced Knowledge Grounding
RaGEP: Rank-aware Geometric Expert Pruning for Mixture-of-Experts Language Models
Anytime-Valid Inference for Online Ranking of Large Language Models
Theory of Minimal Weight Perturbations in Deep Networks and its Applications for Low-Rank Activated Backdoor Attacks
On Expressive Power of Floating-Point Transformers
De4D-SLAM: Gradient-Isolated Static-Dynamic Decoupling for Monocular SLAM in Dynamic Environments
Beyond Static Allocation: Dynamic Sensitivity-Aware Fine-Tuning for Vision Transformers
Simultaneous Multi-objective Alignment Across Verifiable and Non-verifiable Rewards
TimeSAE: Causal Sparse Decoding for Faithful Explanations of Black-Box Time Series Models
MLUBench: A Benchmark for Lifelong Unlearning Evaluation in MLLMs
From Distribution to Geometry: Stable Graph Generalization via Invariant Barycenters
Seg-ReSearch: Segmentation with Interleaved Reasoning and External Search
UniMedVL: Unifying Medical Multimodal Understanding and Generation through Observation-Knowledge-Analysis
Active Exploring like a Pigeon: Reinforcing Spatial Reasoning via Agentic Vision-Language Models
Practical Mechanism for Fault-Tolerant Spiking Neural Networks via Simple Input Control Based on Learnable Fragmentation
HyMTRL: A Hybrid Multi-Task Reinforcement Learning Framework via Phased Policy Evolution
V-ABS: Action-Observer Driven Beam Search for Dynamic Visual Reasoning
Quantifying the noise sensitivity of the Wasserstein metric for images
PanoWorld-X: Generating Explorable Panoramic Worlds via Sphere-Aware Video Diffusion
Temper-Then-Tilt: Principled Unlearning for Generative Models through Tempering and Classifier Guidance
Agent JIT Compilation for Latency-Optimizing Web Agent Planning and Scheduling
ASIR: Steganography for Diffusion Models via Antipodal Sampling and Iterative Recovery
Holi-Spatial: Evolving Video Streams into Holistic 3D Spatial Intelligence
Transitivity Meets Cyclicity: Explicit Preference Decomposition for Dynamic Large Language Model Alignment
RECTOR: Masked Region-Channel-Temporal Modeling for Affective and Cognitive Representation Learning
Informed Asymmetric Actor-Critic: Leveraging Privileged Signals Beyond Full-State Access
Dispersion Loss Counteracts Embedding Condensation and Improves Generalization in Small Language Models
Query Circuits: Explaining How Language Models Answer User Prompts
Cross-Subject Modeling for Widefield Calcium Imaging via Atlas-Aligned Spatiotemporal Tokenization
Balancing Understanding and Generation in Discrete Diffusion Models
Trojan-Speak: Bypassing Constitutional Classifiers with No Jailbreak Tax via Adversarial Finetuning
Towards Context-Invariant Safety Alignment for Large Language Models
Spatio-Temporal LLM: Reasoning about Environments and Actions
Turbo Connection: Reasoning as Information Flow from Higher to Lower Layers
Bio-Inspired Self-Supervised Learning for Wrist-worn Accelerometer Data
Integrated Episodic and Semantic Memory via Modulating Transformer FeedForward Layers
SpikeNet: Sparse Spike-Driven Mask Vector Transformer for Energy-Efficient and Stable Spiking Point Cloud Processing
Mitigating the Modality Gap in Vision–Language Models with Fractal Spectral Geometry
RedDebate: Safer Responses Through Multi-Agent Red Teaming Debates
It's TIME: Towards the Next Generation of Time Series Forecasting Benchmarks
DeltaEvolve: Accelerating Scientific Discovery through Momentum-Driven Evolution
Judging What We Cannot Solve: A Consequence-Based Approach for Oracle-Free Evaluation of Research-Level Math
A Diagnostic Study of Multi-Agent LLMs for Real-World Debates
Attribution-Guided and Coverage-Maximized Pruning for Structural MoE Compression
CONTEXTOR: Contextualized High-order Contrastive Learning
One Step Forward and K Steps Back: Better Reasoning with Denoising Recursion Models
Inference-Time Conformal Reasoning with Valid Factuality Control for Large Language Models
MindFlow: Mind Supernet Powered Thinking Flows for Research Idea Innovation
Neuro-evolutionary Continual Reinforcement Learning
Deterministic Component Mining for Multi-Framework UI2Code Generation
Enhanced Multi-Instance Partial Label Learning via Average Gradient Outer Product
Entropy-Aware Dynamic KV Cache Sparsification for Autoregressive Image Generation and Editing
Towards Optimal Robustness in Learning-Augmented Paging
Algorithmic Recourse of In-Context Learning for Tabular Data
SafeLab: An Interactive High-Fidelity Benchmark for Embodied Safety in Scientific Robotics
One Bug, Hundreds Behind: LLMs for Large-Scale Bug Discovery
Mirror Descent Actor Critic via Bounded Advantage Learning
The Signal is in the Steps: Local Scoring for Reasoning Data Selection
Newton-coupled Dual-Teacher Semi-supervised Learning Framework
Untied Ulysses: Memory-Efficient Context Parallelism via Headwise Chunking
LiMuon: Light and Fast Muon Optimizer for Large Models
OCNR: Stabilizing Self-Play by Mitigating Iteration-Collapse With One-Class Novelty Rewards
TRACER: Persistent Regularization for Robust Multimodal Finetuning
Is Your Diffusion Sampler Actually Correct? A Sampler-Centric Evaluation of Discrete Diffusion Language Models
CL-GCL: Comprehensive and Lightweight Graph Contrastive Learning
Randomized Advantage Transformation (RAT): Computing Natural Policy Gradients via Direct Backpropagation
$\texttt{FlashSchNet}$: Fast and Accurate Coarse-Grained Neural Network Molecular Dynamics
CyberGym-E2E: Scalable Real-World Benchmark for AI Agents' End-to-End Cybersecurity Capabilities
Dissect and Prune: Enhancing Robustness in AI-Generated Image Detection
TQL: Scaling Q-Functions with Transformers by Preventing Attention Collapse
Auditing Sybil: Explaining Deep Lung Cancer Risk Prediction Through Generative Interventional Attributions
PGS: Effective LLM Code Refinement via Property-Oriented and Structurally Minimal Feedback
Left–Right Symmetry Breaking in CLIP-Style Vision-Language Models Trained on Synthetic Spatial-Relation Data
Diagnosing the Reliability of LLM-as-a-Judge via Item Response Theory
FedUSD: Unbiased Synthetic Data for Federated Learning
Doubly Robust Distributionally Robust Offline Contextual Pricing
Graph is a Substrate Across Data Modalities
WorldCompass: Reinforcement Learning for Long-Horizon World Models
Sequential Group Composition: A Window into the Mechanics of Deep Learning
Query Lens: Interpreting Sparse Key-Value Features with Indirect Effects
Convex Dataset Valuation for Post-Training
Making Models Unmergeable via Scaling-Sensitive Loss Landscape
OpenSage: Self-programming Agent Generation Engine
GAE: Unleashing Physical Potential of VLM with Generalizable Action Expert
MuCO: Generative Peptide Cyclization Empowered by Multi-stage Conformation Optimization
A Unified Framework for Diffusion Model Unlearning with f-Divergence
Conflicting Biases at the Edge of Stability: Norm versus Sharpness Regularization
Approximating f -Divergences with Rank Statistics
Long-Context Modeling with Dynamic Hierarchical Sparse Attention for Memory-Constrained LLM Inference
Representation Unlearning: Forgetting through Information Compression
Physics-informed coarsening for multigrid graph neural networks surrogates
Fix the Mind, Not the Move: Interpretable AI Assistance via Knowledge-Gap Localization
Regulating Anatomy-Aware Rewards via Trajectory-Integral Feedback for Volumetric Computed Tomography Analysis
INDEXGUARD: Index-only Backdoor Vetting for Secure Federated PEFT of Large Language Models
Variance-Reduced $(\varepsilon, \delta)-$Unlearning using Forget Set Gradients
CAST: Modeling Visual State Transitions for Consistent Video Retrieval
Learning Global Representation from Queries for Vectorized HD Map Construction
Sample Complexity Bounds for Robust Mean Estimation with Mean-Shift Contamination
PsumQuant: In-line Post-training Partial Sum Quantizer for Energy Efficient NPU Inference
BioFormer: Rethinking Cross-Subject Generalization via Spectral Structural Alignment in Biomedical Time-Series
MotiMotion: Motion-Controlled Video Generation with Visual Reasoning
Unveiling Multi-regime Patterns in SciML: Distinct Failure Modes and Regime-specific Optimization
Distributionally Robust Reinforcement Learning from Human Feedback
Tailoring the Training: Difficulty-Aware Learning Strategy Allocation for Large Language Models
1-Bit Wonder: Improving QAT Performance in the Low-Bit Regime through K-Means Quantization
VLAW: Iterative Co-Improvement of Vision-Language-Action Policy and World Model
The ACUTE Protocol: Operationalizing Language Model Activations for Better Calibration, Utility, and Trust
Are Tools Always Beneficial? Learning to Invoke Tools Adaptively for Dual-Mode Multimodal LLM Reasoning
Advantage Weighted Matching: Aligning RL with Pretraining in Diffusion Models
Decentralized Online Convex Optimization with Efficient Communication: Improved Algorithm and Lower Bounds
Invariant Representation Learning for Source-Free Time Series Forecasting with LLM-Centric Proxy Denoising
Primal-Spectral Generative Modeling: Fast Analytical Generation via Pseudoinverse Lévy Inversion
PolarDepth: Monocular Transparent Object Depth from Polar-Physics Priors
Federated Bilevel Performative Prediction
Differentially Private Geodesic Regression
Smooth Dynamic Cutoffs for Machine Learning Interatomic Potentials
Flow-Based Density Ratio Estimation for Intractable Distributions with Applications in Genomics
Belief Propagation Converges to Gaussian Distributions in Sparsely-Connected Factor Graphs
LLM-based Embeddings: Attention Values Encode Sentence Semantics Better Than Hidden States
Early Decisions Matter: Proximity Bias and Initial Trajectory Shaping in Non-Autoregressive Diffusion Language Models
KineFlow: Kinematic Second-Order Flow Matching for Time-Series Forecasting
Rethinking Generative Image Pretraining: How Far Are We From Scaling Up Next-Pixel Prediction?
BuildArena: A Physics-Aligned Interactive Benchmark of LLMs for Engineering Construction
Coloring the Noise: Adversarial Sobolev Alignment for Faithful Image Super Resolution
Evaluating Language Models in Realistic Conversational Contexts
On Uniform Error Bounds for Kernel Regression under Non-Gaussian Noise
Expanding the AI Evaluation Toolbox with Statistical Models
Offline Multi-agent Continual Cooperation via Skill Partition and Reuse
Test-Time Guidance for Flow-Based Generative Models via Parallel Tempering on Source Distributions
You Don't Protect if You Don't Expect: Breaking the Key Assumption behind CLIP's Test-Time Defenses
Spatial Memory for Out-of-Vision Manipulation in Vision-Language-Action
Linear Ensembles Wash Away Watermarks: On the Fragility of Distributional Perturbations in LLMs
Addressing Instrument-Outcome Confounding in Mendelian Randomization through Representation Learning
Near-Optimal Regret for Policy Optimization in Contextual MDPs with General Offline Function Approximation
Scaling the Scaling Logic: Agentic Meta-Synthesis of Logic Reasoning
Local Hessian Spectral Filtering for Robust Intrinsic Dimension Estimation
Convergence of Two-Timescale Markovian Stochastic Approximations with Applications in Reinforcement Learning
d3LLM: Ultra-Fast Diffusion LLM using Pseudo-Trajectory Distillation
FaPS: A General and Fast Training Method for Diffusion Models
Physics in 2-Steps: Locking Motion Priors Before Visual Refinement Erases Them
FIDIA: Function-Informed Sequence Design via Inference-Aligned Policy Optimization
GUDA: Counterfactual Group-wise Training Data Attribution for Diffusion Models via Unlearning
Distributional Active Inference
Deterministic Inference across Tensor Parallel Sizes That Eliminates Training-Inference Mismatch
Training-Free Adaptation of Diffusion Models via Doob's $h$-Transform
Asymmetric Multi-View Clustering with Hyperbolic Uncertainty Modeling
Sharpness-Aware Minimization Can Hallucinate Minimizers
ERAlign: Energy-based Representation Alignment of GNNs and LLMs on Text-attributed Graphs
What Makes a Representation Good for Single-Cell Perturbation Prediction?
CoPE: Continual Probe-guided Expansion for Large Vision-Language Models
Partial Fusion of Neural Networks: Efficient Tradeoffs Between Ensembles and Weight Aggregation
MDGMIX: Boundary-Aware Subgraph Mixing for Multi-Domain Graph Pre-Training
Spectrally-Guided Diffusion Noise Schedules
Structured Multi-step Jailbreaking under a Hamiltonian Generative Formulation
CyberJurors: A Multi-Agent Simulation Task for E-Commerce Disputes Verdict
Scaling the Prior: Size-Consistent Geometric Diffusion for 3D Molecular Generation
ProMiSE: Protein Multi-State Evaluation Benchmark in Biological Contexts
DeepHA: Scaling Action Chains Elicits Deep Hierarchical Agents
Consistency Deep Equilibrium Models
Fast k-means Seeding Under The Manifold Hypothesis
Adaptively Robust Resettable Streaming
A Geometric Analysis of Small-sized Language Model Hallucinations
SpecExit: Accelerating Large Reasoning Model via Speculative Exit
Simple Policy Gradients for Reasoning with Diffusion Language Models
GEMQ: Global Expert-Level Mixed-Precision Quantization for MoE LLMs
TRAP: Hijacking VLA CoT-Reasoning via Adversarial Patches
How Language Models Process Negation
Partitioning for Intrinsic Model Inversion Resistance in Collaborative Inference
MIMO-LP: A Multi-Input Multi-Output Framework for Subgraph-based Link Prediction
Deliberate Evolution: Agentic Reasoning for Sample-Efficient Symbolic Regression with LLMs
Thinking in Latent Space: Progressive Multimodal Simplification for Visual Reasoning
TextME: Bridging Unseen Modalities Through Text Descriptions
RAD: Retrieval High-quality Demonstrations to Enhance Decision-making
Regret Minimization With a Crowd of Awakening Experts
Emergence of Biased Consensus in Multi-Agent LLM Debates
Calibrating Decision Robustness via Inverse Conformal Risk Control
AdvEvo-MARL: Shaping Internalized Safety through Adversarial Co-Evolution in Multi-Agent Reinforcement Learning
From Poisoned to Aware: Fostering Backdoor Self-Awareness in LLMs
PerceptionRubrics: Calibrating Multimodal Evaluation to Human Perception
Robust AI Evaluation through Maximal Lotteries
From Absolute to Relative: Rethinking Reward Shaping in Group-Based Reinforcement Learning
On Minimum Depth and Width of Floating-Point Neural Networks for Representing Floating-Point Functions
The Perceptual Bandwidth Bottleneck in Vision-Language Models: Active Visual Reasoning via Sequential Experimental Design
Stop Training for the Worst: Progressive Unmasking Accelerates Masked Diffusion Training
Progressive Cramming: Reliable Token Compression and What It Reveals
From Evaluation to Design: Using Potential Energy Surface Smoothness Metrics to Guide ML Interatomic Potential Architectures
Focus-Then-Contact: Speeding Up Robotic Contact-Rich Task Learning with Affordance-Guided Real-World Residual Reinforcement Learning
CORE: Conflict-Oriented Reasoning for General Multimodal Manipulation Detection
SPA: A Simple but Tough-to-Beat Baseline for Knowledge Injection
WinQ: Accelerating Quantization-Aware Training of Language Models Around Saddle Points
Contextual Slate GLM Bandits with Limited Adaptivity
Adaptive Code Watermarking Through Reinforcement Learning
The Value Function Semi-Algebraic Set in Partially Observable Markov Decision Processes
KernelFoundry: Hardware-Aware Evolutionary GPU Kernel Optimization
(Doubly) Exponential Lower Bounds for Follow the Regularized Leader in Potential Games
Resting Neurons, Active Insights: Robustifying Activation Sparsity in LLMs via Spontaneity
Homophily-Heterogeneity Gradient Surgery for Federated Graph Learning
Temporal-Aware Reasoning Optimization for Video Temporal Grounding
Video-Based Optimal Transport for Feedback-Efficient Offline Preference-Based Reinforcement Learning
LAST: Bridging Vision-Language and Action Manifolds via Gromov-Wasserstein Alignment
Training-Free Hashing-Based Attention via Binary Principal Components
Sample-Efficient Diffusion-based Reinforcement Learning with Critic Guidance
Deep Coupling Learning for Solving PDEs
ExCyTIn-Bench: Evaluating LLM agents on Cyber Threat Investigation
Semi-Supervised Neural Super-Resolution for Mesh-Based Simulations
RiskZero: Plan More to Risk Less with a Learned Model
VT-Bench: A Unified Benchmark for Visual-Tabular Multi-Modal Learning
Chain-of-Goals Hierarchical Policy for Long-Horizon Offline Goal-Conditioned RL
Less Token, More Signal: MoE Expert Pruning via Critical Token Selection
SpaceVista: All-Scale Visual Spatial Reasoning from mm to km
MoSA: Motion-constrained Stress Adaptation for Mitigating Real-to-Sim Gap in Continuum Dynamics via Learning Residual Anisotropy
Scaling Continual Learning to 300+ Tasks with Bi-Level Routing Mixture-of-Experts
Benchmarking Dense and Indiscernible Object Counting with Blueberries
Shift-Dependent Asymmetry: Orthogonal Inverse Low-Rank Adaptation for Federated Medical Segmentation
Veda: Scalable Video Diffusion via Distilled Sparse Attention
AgentConductor: Topology Evolution for Multi-Agent Competition-Level Code Generation
Compass-RoPE: Isotropic Rotary Position Embeddings for Vision Transformers
MoshiRAG: Asynchronous Knowledge Retrieval for Full-Duplex Speech Language Models
Visual Persuasion: What Influences Decisions of Vision-Language Models?
What If We Let Forecasting Forget? A Sparse Bottleneck for Cross-Variable Dependencies
BASIL: Scalable Bayesian Semi-supervised Clustering with Feature Selection and Adaptive Constraint Weighting
TABX: A High-Throughput Sandbox Battle Simulator for Multi-Agent Reinforcement Learning
Attacking Gray-Box Large Vision-Language Models with Adaptive SVD-Structured Adversarial Alignment
Adaptive Multiscale Binary Expansion Tests for Independence
ReLAM: Learning Anticipation Model for Rewarding Visual Robotic Manipulation
Opt-Miner: Empowering Information-Seeking Agent with Tree-Guided Data Synthesis for Optimization Modeling
Jailbreaking Vision-Language Models Through the Visual Modality
Learning Decentralized LLM Collaboration with Multi-Agent Actor Critic
Connecting Independently Trained Modes via Layer-Wise Connectivity
Dynamic Stratified Contrastive Learning with Upstream Augmentation for MILP Branching
Modality-Decoupled Online Recursive Editing
Capacitated Fair-Range Clustering: Hardness and Approximation Algorithms
CMI-RewardBench: Evaluating Music Reward Models with Compositional Multimodal Instruction
Approximate Proportionality in Online Fair Division
REVIS: Sparse Latent Steering to Mitigate Object Hallucination in Large Vision-Language Models
Problem Distributions as Tasks: Repurposing Meta Learning for Generative Combinatorial Optimization towards Multi-task Pretraining and Adaptation
How do Humans Process AI-generated Hallucination Contents: a Neuroimaging Study
Why Do We Need Warm-up? A Theoretical Perspective
Rethinking Visual Autoregressive Sampling with Information-Grounding Guidance
Energy-Structured Low-Rank Adaptation for Continual Learning
RVAS: Referring Video Active Exploration and Segmentation
DECO: Decoupled Multimodal Diffusion Transformer for Bimanual Dexterous Manipulation with a Plugin Tactile Adapter
Reasoning Quality Emerges Early: Data Curation for Reasoning Models
Graph-R1: Towards Agentic GraphRAG Framework via End-to-end Reinforcement Learning
Learning to Discover at Test Time
Towards a Science of AI Agent Reliability
Simple Algorithms for Bad Triangle Transversals with Applications to Correlation Clustering
Credit-assigned Policy Gradient for Early Stage Retrieval in Two-stage Ranking
NAVIGATE: Evaluating Visual-Guided Search Decision-Making on the Open Web
CaP-X: A Framework for Benchmarking and Improving Coding Agents for Robot Manipulation
Resolution as a Direction: Vector-Panning Feature Alignment for Cross-Resolution Re-Identification
Discovering Symmetry Groups with Flow Matching
PathWise: Planning through World Model for Automated Heuristic Design via Self-Evolving LLMs
LIF Recurrent Memory Enables Long-Horizon Spiking Computation
When and How Human Curation Backfires: Preference Alignment under Multi-Model Self-Consuming Loop
ProConMV: Provenance-Enabled Conceptual Framework for Interpretable Multi-View Diabetic Retinopathy Diagnosis
Evolving Interdependent Operators with Large Language Models for Multi-Objective Combinatorial Optimization
Thinking in Flow: A Dissipative Stabilization Operator for Robust Autoregressive Reasoning
ExpWeaver: LLM Agents Learn from Experience via Latent RAG
Old Habits Die Hard: How Conversational History Geometrically Traps LLMs
Score Correction for Generative Models with Probabilistic Constraints
Elastic Diffusion Transformer
Text Generation as Continuous Latent Dynamics via Reinforcement Learning
PoMtVRS: Preference-Optimized Multi-Task Vehicle Routing Solver with Preference Gating
Towards Understanding Continual Factual Knowledge Acquisition of Language Models: From Theory to Algorithm
LongCoT: Benchmarking Long-Horizon Chain-of-Thought Reasoning
From Volume to Value: Preference-Aligned Memory Construction for On-Device RAG
Trajectory-Aware Certified Decentralized Unlearning via SGD Stability
EqGINO: Equivariant Geometry-Informed Fourier Neural Operators for 3D PDEs
OptiFluence: Principled Design of Privacy Canaries
D$^2$O: A Dual Debiasing Operator for Training-Free Test-Time Adaptation of Vision–Language Models
Efficiently Learning Drifting Halfspaces with Massart Noise
Cerebellar-Inspired Residual Control for Fault Recovery: From Inference-Time Adaptation to Structural Consolidation
PISCES: Annotation-free Text-to-Video Post-Training via Optimal Transport-Aligned Rewards
Riemannian Optimization for Fair Spectral Clustering
ECCO: Evidence-Driven Causal Reasoning for Compiler Optimization
Evolving Quantitative Reasoning through Self-Play in Digital Twin Markets
Curriculum Reinforcement Learning for Black-Box Prompt Tuning via Large Language Models
A General Neural Backbone for Mixed-Integer Linear Optimization via Dual Attention
Monitorability as a Free Gift: How RLVR Spontaneously Aligns Reasoning
The Generalization Spectrum: A Chromatographic Approach to Evaluating Learning Algorithms
dLLM-Cache: Accelerating Diffusion Large Language Models with Adaptive Caching
Towards Fully Parameter-Free Stochastic Optimization: Grid Search with Self-Bounding Analysis
ComplexMCP: Evaluation of LLM Agents in Dynamic, Interdependent, and Large-Scale Tool Sandbox
Dimension-Free Multimodal Sampling via Preconditioned Annealed Langevin Dynamics
MoSSP: A Momentum-Based Single-Loop Stochastic Penalty Method for Nonconvex Constrained DC-regularized Optimization
VecDesigner: Exploring Visual Guidance and Structural Consistency for Semantic Typography
Finding the Minimal Parameter Budget for Implicit Reasoning: A Data Complexity Driven Scaling Law for Language Models
Draft-and-Audit Reinforcement Learning for Optimization Modeling
RAPNet: Accelerating Algebraic Multigrid with Learned Sparse Corrections
Certifying Graph Neural Networks Against Label and Structure Poisoning
Gradients with Respect to Semantics Preserving Embeddings Tell the Uncertainty of Large Language Model
Systematic Failures in Collective Reasoning under Distributed Information in Multi-Agent LLMs
Understanding Behavior Cloning with Action Quantization
Dual-View Predictive Diffusion: Lightweight Speech Enhancement via Spectrogram-Image Synergy
Bias-Spectrum Neural Processes for Parametric PDEs: Architecture Priors Meet PDE Constraints
Normality Calibration in Semi-supervised Graph Anomaly Detection
Rethinking the Design Space of Reinforcement Learning for Diffusion Models: On the Importance of Likelihood Estimation Beyond Loss Design
ReMoE: Boosting Expert Reuse through Router Fine-Tuning in Memory-Constrained MoE LLM Inference
Provable Training Data Identification for Large Language Models
MechVQA: Benchmarking and Enhancing Multimodal LLMs on Comprehensive Mechanical Drawing Understanding
Innovation: An Almost Characterization of Hallucination
MAnchors: Memorization-Based Acceleration of Anchors via Rule Reuse and Transformation
Resilient Coresets and Clustering
How Far Ahead Do LLMs Plan? Uncovering the Latent Horizon in Chain-of-Thought Reasoning
From Coarse to Fine: Deep Prototype Refinement Network for Few-Shot Point Cloud Semantic Segmentation
SVD as a Fast Interpretability Method for Transformers
TopAdapter: Topology-Aware Prompt Tuning for Efficient Point Cloud Understanding
Enhancing Cross-subject Emotion Recognition via Heterogeneous Distribution Augmentation and Collaborative Learning
Diffusion Language Model Parallel Decoding via Product-of-Experts Bridge
From Similarity to Vulnerability: Key Collision Attack on LLM Semantic Caching
Accurate, Private, Secure, Federated U-statistics with Higher Degree
GLARE: Scalable Neuro-Symbolic Reward Shaping for LLM Agents via Group-Level Automata
Evolution Strategies at Scale: LLM Fine-Tuning Beyond Reinforcement Learning
How does Bayesian Sampling help Membership Inference Attacks?
A Distributional View for Visual Mechanistic Interpretability: KL-Minimal Soft-Constraint Principle
Fix the Loss, Not the Radius: Rethinking the Adversarial Perturbation of Sharpness-Aware Minimization
Preference-Calibrated Optimization with Score-Level Distribution Alignment for Text-to-Image Diffusion Model Unlearning
One-Step Residual Shifting Diffusion for Image Super-Resolution via Distillation
Decoupling Reasoning and Confidence: Resurrecting Calibration in Reinforcement Learning from Verifiable Rewards
DRL-STAF: A Deep Reinforcement Learning Framework for State-Aware Forecasting of Complex Multivariate Hidden Markov Processes
DREAM-R: Multimodal Speculative Reasoning with RL-Based Refined Drafting, Precise Verification, and Fully Parallel Execution
Noisy-Space Policy Gradient for Diffusion Policies in Offline Reinforcement Learning
Fleet: Few Shots Lead Effective AI-generated Image Detection
Align Your Trajectory Tangent: Training Better Consistency Models via Manifold-Aligned Tangents
AMDP: Asynchronous Multi-Directional Pipeline Parallelism for Large-Scale Models Training
CalPro: Prior-Aware Evidential Conformal Prediction with Structure-Aware Sensitivity Bounds for Protein Structures
Inner-layer Token Self-modulation as Another Scaling Axis for LLMs
CoIRL-AD: Collaborative-Competitive Imitation-Reinforcement Learning in Latent World Models for Autonomous Driving
PathwayLLM: Explainable Clinical Trajectory Modeling with Structured Pathways for Sepsis Prediction
Locally Coherent Parallel Decoding in Diffusion Language Models
Sparse but Wrong: Incorrect L0 Leads to Incorrect Features in Sparse Autoencoders
Lower Bounds for Frank-Wolfe on Strongly Convex Sets
SPEAR: A Unified SSL Framework for Learning Speech and Audio Representations
SCalDA: Semantics-Calibrated and Diffusion-Enhanced Data Augmentation
Partial Ring Scan: Revisiting Scan Order in Vision State Space Models
pTNAS: Progressive Neural Architecture Search for Tabular Data
Towards a Holistic Understanding of Selection Bias for Causal Effect Identification
PPDL: LLM-Based Flows as Probabilistic Programs
Geometrically Constrained Stenosis Editing in Coronary Angiography via Entropic Optimal Transport
Learning to Memorize with Attributive and Associative Memory for Online Test-Time Adaptation of Vision-Language Models
Why Specialist Models Still Matter: A Heterogeneous Multi-Agent Paradigm for Medical Artificial Intelligence
REG: In-Sample RL via Regularizing the Evaluation Gap
CoopEval: Benchmarking Cooperation-Sustaining Mechanisms and LLM Agents in Social Dilemmas
Anytime Detection of Strategic Deviations in Multi-Agent Systems
High-Fidelity ANN-to-SNN Conversion via Closed-Loop CKA Distillation
Ekka: Automated Diagnosis of Silent Errors in LLM Inference
GraphPFN: A Prior-Data Fitted Graph Foundation Model
Probing Cross-modal Information Hubs in Audio-Visual LLMs
Exploring and Exploiting Stability in Latent Flow Matching
MoST: Mixing Speech and Text with Modality-Aware Mixture of Experts
PhotoAgent: Exploratory Visual Aesthetic Planning with Large Vision Models
Efficient Preference Poisoning Attack on Offline RLHF
Convergence Analysis of the Lion Optimizer in Centralized and Distributed Settings
Weaving in the Clouds: Achieving Synergistic Collaboration among LLM Agents via Federated Learning
BiRQA: Bidirectional Robust Quality Assessment for Images
An Odd Estimator for Shapley Values
Sampling and Identity-Testing Without Approximate Tensorization of Entropy
Being More Lightweight and Practical: Mini-sized Contrastive Learning Pre-trained Models for Fine-grained Traffic Task
Taming Aleatoric Impulse in Off-Policy Reinforcement Learning
The Abstraction Gap in Vision-Language Causal Reasoning
Watermarking LLM Agent Trajectories
JANUS-LORA: A Balanced Low-Rank Adaptation for Continual Learning
Beyond ReLU: Bifurcation, Oversmoothing, and Topological Priors
Reward and Guidance through Rubrics: Promoting Exploration to Improve Multi-Domain Reasoning
Inference of Online Newton Methods with Nesterov's Accelerated Sketching
Heterogeneous Customizable Personalized Federated Fine-Tuning Approach for Large Language Models
DR-MMSearchAgent: Deepening Reasoning in Multimodal Search Agents
BioAgent Bench: An AI Agent Evaluation Suite for Bioinformatics
A Two-Tier Perspective on Inference-Time Parallelism in Multi-Agent LLM Systems
Dimension-Independent Convergence of Underdamped Langevin Monte Carlo in KL Divergence
LSGQuant: Layer-Sensitivity Guided Quantization for One-Step Diffusion Real-World Video Super-Resolution
Evaluating Robustness of Reasoning Models on Parameterized Logical Problems
PINE: Pruning Boosted Tree Ensembles with Conformal In-Distribution Prediction Equivalence
Sharper Generalization Guarantees for Asynchronous SGD: Beyond Lipschitzness, Smoothness and Data Homogeneity
Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers
Flow Equivariant World Models: Structured Memory for Dynamic Environments
Learning to Correct: Reinforcement Learning for Multi-Attempt Chain-of-Thought
Test-Time Graph Search for Goal-Conditioned Reinforcement Learning
LALM-as-a-Judge: Benchmarking Large Audio-Language Models for Safety Evaluation in Multi-Turn Spoken Dialogues
Does Math Reasoning Improve General LLM Capabilities? Understanding Transferability of LLM Reasoning
AC-ODM: Actor–Critic Online Data Mixing for Sample-Efficient LLM Pretraining
AutoSizer: Automatic Sizing of Analog and Mixed-Signal Circuits via Large Language Model (LLM) Agents
FullStack-Agent: Enhancing Agentic Full-Stack Web Coding via Development-Oriented Testing and Repository Back-Translation
Extending Fair Null-Space Projections for Continuous Attributes to Kernel Methods
DSGym: A Standardized and Holistic Framework for Evaluating and Training Data Science Agents
A Risk Decomposition Framework for Pre-hoc Fine-tuning Prediction
Capability Traps in DPO
MEDUSA: Motion Elimination in Diffusion Using Spectral Attack
CrispEdit: Low-Curvature Projections for Scalable Non-Destructive LLM Editing
TileSparse: Arithmetic-Intensity-Aware Sparse Attention for Compute-Bound LLM Decoding
From Per-Image Low-Rank to Encoding Mismatch: Rethinking Feature Distillation in Vision Transformers
Learn to Think: Improving Multimodal Reasoning through Vision-Aware Self-Improvement Training
Hierarchical Policy Learning via Spectral Decomposition
Good SFT Optimizes for SFT, Better SFT Prepares for Reinforcement Learning
Fast Reconstruction of Mixtures of Bernoulli Product Distributions
Gradient Smoothing: Coupling Layer-wise Updates for Improved Optimization
From Noise to Control: Parameterized Diffusion Policies
Constrained Adaptive Rejection Sampling
Refining Context-Entangled Content Segmentation via Curriculum Selection and Anti-Curriculum Promotion
Pessimistic Verification for Open-Ended Math Questions
BRIDGE: Predicting Human Task Completion Time From Model Performance
HGMem: Hypergraph-based Working Memory to Improve Multi-step RAG for Long-Context Complex Relational Modeling
BVS: Bayesian Visual Search with Multimodal Large Language Model for Fine-grained Perception
DDP-WM: Disentangled Dynamics Prediction for Efficient World Models
StructMamPose: From Sequential Perception to Structural Reasoning for 3D Human Pose Estimation
Generalized Correctness Models: Learning Calibrated and Cross-Model Correctness Predictors from Historical Patterns
From Weak Cues to Real Identities: Evaluating Inference-Driven De-Anonymization in LLM Agents
POLCA: Stochastic Generative Optimization with LLM
NeurOCNN: A Neural-Operator-Based Model for Physiological Time Series
Target-Driven Policy Optimization for Sequential Counterfactual Outcome Control
Two-Parameter Flows for Learning Population Dynamics of Physical Systems
Boosting World Models Learning via Latent-Space Value Alignment
CRAG: Can 3D Generative Models Help 3D Assembly?
Hard-Constrained Graph Generation with Discrete-Projection Diffusion
Reasoning Models Struggle to Control their Chains of Thought
Fine-Tuning Masked Diffusion for Provable Self-Correction
Train for Truth, Keep the Skills: Binary Retrieval-Augmented Reward Mitigates Hallucinations
Bring My Cup! Personalizing Vision-Language-Action Models with Visual Attentive Prompting
Securing Multimodal AI through Internal Information Decomposition
DiscoForcing: A Unified Framework for Real-Time Audio-Driven Character Control with Diffusion Forcing
Process Reward Agents for Steering Knowledge-Intensive Reasoning
Fair Dataset Distillation via Cross-Group Barycenter Alignment
OpenDeception: Learning Deception and Trust in Human–AI Interaction via Multi-Agent Simulation
A Very Big Video Reasoning Suite
Memory-Distilled Selection for Noise-Robust Anomaly Detection
AgentSuite: Toward More Reliable Agent Evaluation with a Component-Based Benchmark Auditing Pipeline
cuRegOT: A GPU-Accelerated Solver for Entropic-Regularized Optimal Transport
Structurally Aligned Subtask-Level Memory for Software Engineering Agents
miniF2F-Dafny: LLM-Guided Mathematical Theorem Proving via Auto-Active Verification
Maximum-Likelihood Learning of Latent Dynamics Without Reconstruction
Training-Free Vector Quantization via Gaussian VAEs
Weak Diffusion Priors Can Still Achieve Strong Inverse-Problem Performance
Rethinking Human Intent-to-CAD: Parametric CAD Model Generation via Cooperative Multi-Task Alignment and Spatial-Aware Reinforcement Learning
Infinite-World: Scaling Interactive World Models to 1000-Frame Horizons via Pose-Free Hierarchical Memory
Understanding Transfer Learning of RNA Foundation Models on Downstream Tasks
MotionMAR: Multi-scale Auto-Regressive Human Motion Reconstruction from Sparse Observations
Joint-Embedding Predictive Learning of Latent Market States in U.S. Equities
Online Robust Reinforcement Learning with General Function Approximation
A Unifying Relational Perspective on Expressive Lottery Tickets
LOTTERY: Learning from Reference-Only Samples in Two-Sample Testing under Size Asymmetry
Cure-SFT: Diagnostic-Guided Data Curation for Instruction Tuning
Endogenous Resistance to Activation Steering in Language Models
TRIM: Token-wise Attention-Derived Saliency for Data-Efficient Instruction Tuning
Relighting as a Probe of Visual Priors via Augmented Latent Intrinsics
STARE: Step-wise Temporal Alignment and Red-teaming Engine for Multi-modal Toxicity Attack
Hierarchical Causal Abduction: A Foundation Framework for Explainable Model Predictive Control
Self-supervised Hierarchical Visual Reasoning with World Model
SpreadsheetArena: Decomposing Preference in LLM Generation of Spreadsheet Workbooks
Debate with Images: Detecting Deceptive Behaviors in Multimodal Large Language Models
Risk-Averse and Optimistic Advertiser Incentive Compatibility in Auto-bidding
Model-Dowser: Data-Free Importance Probing to Mitigate Catastrophic Forgetting in Multimodal Large Language Models
CVE-Factory: Scaling Expert-Level Agentic Tasks for Code Security Vulnerability
CAffNet: Hard Constraint-Affine Neural Networks
The Convergent Representation of Contrastive Vision-Language Models: Geometry, Modality Gap and Shared Space Alignment
Task-Aware Structured Memory for Dynamic Multi-modal In-Context Learning
$\text{DT}^\text{2}$: Decision-Targeted Digital Twins
RQ-MoE: Residual Quantization via Mixture of Experts for Efficient Input-Dependent Vector Compression
Advancing Analytic Class-Incremental Learning through Vision-Language Calibration
Kuramoto Oscillatory Phase Encoding: Neuro-inspired Synchronization for Improved Learning Efficiency
Learning to Execute Graph Algorithms Exactly with Graph Neural Networks
REAL: Resolving Knowledge Conflicts in Knowledge-Intensive Visual Question Answering via Reasoning-Pivot Alignment
LEGO-FL: Learning Heterogeneous Federated Models as a LEGO Assembly Games
Efficient Prediction of SO(3)-Equivariant Hamiltonian Matrices via SO(2) Local Frames
Set-Preserving Calibration from Conformal P-Values to E-Values
Large Scale Manifold Balanced Clustering
Utonia: Toward One Encoder for All Point Clouds
Building Reliable Long-Form Generation via Hallucination Rejection Sampling
CoCoQuant: Breaking the Bandwidth Wall via Co-Optimized Communication and Computation Quantization
Blending Neural Control Density Functions for Stabilization and Safety
Reasoning Theater: Disentangling Model Beliefs from Chain-of-Thought
Interventional Processes For Causal Uncertainty Quantification
Shared Lexical Task Representations Explain Behavioral Variability In LLMs
Semantic Integrity Matters: Benchmarking and Preserving High-Density Reasoning in KV Cache Compression
Fisher-Preserving Guidance: Training-Free Manifold Constraints for Safe Diffusion Control
Confidence is Not Universal: Task-Dependent Calibration and Emergent Behavior in LLMs
How does information access affect LLM monitors' ability to detect sabotage?
RSTR: Reducing SpatioTemporal Redundancy in Diffusion Transformers
AI Engram: In Search of Memory Traces in Artificial Intelligence
De-attribute to Forget for LLM Unlearning
MemIncept: Steering LLM Agents via Cooperative Stealthy Memory Injections
FiSeR: Fine-Grained Source Representations for Cross-Domain AI Image Detection
AD-MIR: Bridging the Gap from Perception to Persuasion in Advertising Video Understanding via Structured Reasoning
ArenaRL: Scaling RL for Open-Ended Agents via Tournament-based Relative Ranking
The Illusion of Generalization in Tabular Language Models
Agent World Model: Infinity Synthetic Environments for Agentic Reinforcement Learning
Covariance estimation using Markov chain Monte Carlo
GFedCL: Graph-Based Federated Continual Learning with Spatial and Temporal Awareness
From Out-of-Distribution Detection to Hallucination Detection: A Geometric View
Manifold-Optimal Guidance: A Unified Riemannian Control View of Diffusion Guidance
Joint-Space Empowerment as a Theory of Dexterous Motor Coordination
Learning Efficient Guardrails for Compliance
TAG: Tangential Amplifying Guidance for Hallucination-Resistant Sampling
SleepMaMi: A Universal Sleep Foundation Model for Integrating Macro- and Micro-structures
Reflector: Internalizing Step-wise Reflection against Indirect Jailbreaks
Clarify Before You Draw: Proactive Agents for Robust Text-to-CAD Generation
Non-Adversarial Imitation Learning Provably Free of Compounding Errors: The Value Flow Mechanism
What Does Flow-Matching Bring to TD-Learning?
Opportunistic Expert Activation: Batch-Aware Expert Routing for Faster Decode Without Retraining
When RL Meets Adaptive Speculative Training: A Unified Training-Serving System
Fox in the Henhouse: Supply-Chain Backdoor Attacks Against Reinforcement Learning
OpenHA: A Series of Open-Source Hierarchical Agentic Models in Minecraft
Taming the Recent-Data Bias: Towards Robust Time Series Forecasting with Global Context
Unified Time Series Explanations via Amortized Optimization and Instance-level Multi-Expert Knowledge Distillation
CauchyNet: Compact and Data-Efficient Learning using Holomorphic Activation Functions
$G^2$-Reader: Dual Evolving Graphs for Multimodal Document QA
OptProver: Bridging Olympiad and Optimization through Continual Training in Formal Theorem Proving
Factored Gossip DiLoCo: Reducing Blocking Communication within DiLoCo
NEMO: Execution-Aware Optimization Modeling via Autonomous Coding Agents
FedRGL: Robust Federated Graph Learning under Label Noise
One-shot Conditional Sampling: MMD meets Nearest Neighbors
DC-LA: Difference-of-Convex Langevin Algorithm
Predicting What Matters: Robust Generalist Robot Policy Learning via Future Semantic Mask
LabBuilder: Protocol-Grounded 3D Layout Generation for Interactable and Safe Laboratory
Reinforcement Learning with Evolving Rubrics for Deep Research
PLASH: Provably Linear-Time Attention with Selective Higher-Order Feature Sketching
Supervise Less, See More: Training-free Nuclear Instance Segmentation with Prototype-Guided Prompting
Bridging Functional and Representational Similarity via Usable Information
Learning Hamiltonian Dynamics at Scale: A Differential-Geometric Approach
Incremental Transformer Neural Processes
MODEL SOUPS NEED ONLY ONE INGREDIENT
DNACHUNKER: Learnable Tokenization for DNA Language Models
AI4SLT: Empirical Processes in Lean 4 for Formal Statistical Learning Theory
Randomized Feasibility Methods for Constrained Optimization with Adaptive Step Sizes
CFPO: Counterfactual Policy Optimization for Multimodal Reasoning
Learning to Search and Searching to Learn for Generalization in Planning
Order within Chaos: Capturing Intrinsic Energy Anomalies for AI-Manipulated Image Forgery Localization
PEARL: Differentially Private and Entropy-Aware Regulated Language Generation
A Two-Layer Framework for Joint Online Configuration Selection and Admission Control
LipoPU: Pocket-level Prediction of Lipid-Protein Interactions via Positive-Unlabeled Learning
TACTIC: Task-Aware Sparse Coordination Graphs for Multi-Task Multi-agent Reinforcement Learning
Learning Taxonomic Trees with Hierarchical Representation Regularization for Large Multimodal Models
Markov Chain Monte Carlo without Evaluating the Target: an Auxiliary Variable Approach
Structure-Induced Information for Rerooting Levin Tree Search
Unveiling the Potential of Quantization with MXFP4: Strategies for Quantization Error Reduction
Stochastic Order Learning: An Approach to Rank Estimation Using Noisy Data
MoSE: Mixture of Slimmable Experts for Efficient and Adaptive Language Models
IO-Adam: Rethinking Memory-Efficient Adaptive Optimizers from Gradient Computation
Disease-Centric Vision-Language Pretraining with Hybrid Visual Encoding for 3D Computed Tomography
Spherical Procrustes Alignment for Reliable Medical Audio Diagnosis
VFMF: Dense Forecasting by Generating Foundation Model Features
Efficient Generative Modeling beyond Memoryless Diffusion via Adjoint Schrödinger Bridge Matching
Float8@2bits: Entropy Coding Enables Data-Free Model Compression
Geometric Entropy and Retrieval Phase Transitions in Continuous Thermal Dense Associative Memory
DecoderTCR: Compositional Pretraining and Entropy-Guided Decoding for TCR-pMHC Interactions
CoCoReviewBench: A Completeness- and Correctness-Oriented Benchmark for AI Reviewers
GenExam: A Multidisciplinary Text-to-Image Exam
Federated Learning with Unlabeled Clients: Personalization Can Happen in Low Dimensions
Hide&Seek: Learning to Explain in an End-to-End Differentiable Network
Directional Neural Collapse Explains Few-Shot Transfer in Self-Supervised Learning
Learning to Route Languages for Multilingual Policy Optimization
Decomposing Query-Key Feature Interactions Using Contrastive Covariances
Optimal Anytime Algorithms for Online Convex Optimization with Adversarial Constraints
LUCID: Attention with Preconditioned Representations
From Drift to Coherence: Stabilizing Beliefs in LLMs
GeoPT: Scaling Physics Simulation via Lifted Geometric Pre-Training
VENOMREC: Cross-Modal Interactive Poisoning for Targeted Promotion in Multimodal LLM Recommender Systems
One-shot Entropy Minimization for Language Model Reasoning
PADD: Path-Aligned Decompression Distillation for Non-Router Teacher to Guide MoE Student Learning
CLAA: Cross-Layer Attention Aggregation for Accelerating LLM Prefill
PrivCode++: Latent-Conditioned Differentially Private Code Generation for Comprehensive Guarantees
Demystifying Mergeability: Interpretable Properties to Predict Model Merging Success
Safe Reinforcement Learning with Preference-based Constraint Inference
Disentangling Consensus and Value-Specific Representations for Controllable Pluralistic Value Alignment of LLMs
R$^3$L: Reasoning 3D Layouts from Relative Spatial Relations
Representation Drift Compensation: A Near-Zero Inference Cost Enhancement for LLM Decomposition
CombinationTS: A Modular Framework for Understanding Time-Series Forecasting Models
MetaOthello: A Controlled Study of Multiple World Models in Transformers
VideoSEG-O3: A Multi-turn Reinforcement Learning Framework for Reasoning Video Object Segmentation
TriAttention: Efficient Long Reasoning with Trigonometric KV Compression
You Can Learn Tokenization End-to-End with Reinforcement Learning
SWE-fficiency: Can Language Models Optimize Real-World Repositories on Real Workloads?
Do Text Edits Generalize to Visual Generation? Benchmarking Cross-Modal Knowledge Editing in UMMs
Counterfactual Bootstrap for Robust Meta-Reinforcement Learning
SPARC: Separating Perception And Reasoning Circuits for Test-time Scaling of VLMs
Incomplete Multi-View Clustering via Neighborhood-Conditioned Diffusion
PADS-TAL: Padding-Annealed Diffusion Sampling in Text-Aware Latent Space for Robust and Diverse Text-to-Music Generation
ScDiVa: Masked Discrete Diffusion for Joint Modeling of Single-Cell Identity and Expression
SceneDirector: Bridging Explicit Geometry and Generative Priors for Unified Driving Scene Editing
Learning to Reason for Factuality
Reason, Then Re-reason: Cross-view Revisiting Improves Spatial Reasoning
Sign Lock-In: Randomly Initialized Weight Signs Persist and Bottleneck Sub-Bit Model Compression
Numina-Lean-Agent: An Open and General Agentic Reasoning System for Formal Mathematics
WinDeskGround: A Benchmark for Robust GUI Grounding in Complex Multi-Window Desktop Environments
Navigating the Pareto Frontier of Alignment: Spectrum-Adaptive Fine-Tuning for LLMs
PRISM: Training-Free Video Anomaly Detection via Intrinsic Statistical Modeling
Think in Latent, Explain in Language: Self-Explainable Latent Reasoning
Training AI Co-Scientists Using Rubric Rewards
AudioChat: Unified Audio Storytelling, Editing, and Understanding with Transfusion Forcing
A Geometry-Aware Efficient Algorithm for Compositional Entropic Risk Minimization
SciNet: Evaluating AI Agents in Relation-Aware Scientific Literature Retrieval
MAST: Motif-Augmented Diffusion with Search Tree for Spectroscopic Molecular Structure Elucidation
Exposing Vulnerabilities in Explanation for Time Series Classifiers via Dual-Target Attacks
FedReLa: Imbalanced Federated Learning via Re-Labeling
Are VLMs Seeing or Just Saying? Uncovering the Illusion of Visual Re-examination
LRAgent: Efficient KV Cache Sharing for Multi-LoRA LLM Agents
TCAP: Tri-Component Attention Profiling for Unsupervised Backdoor Detection in MLLM Fine-Tuning
Can local learning match self-supervised backpropagation?
Multimodal Crystal Flow: Any-to-Any Modality Generation for Unified Crystal Modeling
Reflective Hamiltonian Monte Carlo: Mixing Analysis and Application to Sampling on Stiefel Manifold
Phy-CoSF: Physics-Guided Continuous Spectral Fields Reconstruction and Spectral Super-Resolution for Snapshot Compressive Imaging
SciAgentGym: Benchmarking Multi-Step Scientific Tool-Use in LLM Agents
Reliability-Aware LLM Alignment from Inconsistent Human Feedback
FoundObj: Self-supervised Foundation Models as Rewards for Label-free 3D Object Segmentation
Beyond Pixels: Mining Compressed Domain Artifacts for Efficient AI-Generated Video Detection
Unlearning with Asymmetric Sources: Improved Unlearning-Utility Trade-off with Public Data
Diversity-Driven Offline Multi-Objective Optimization via Nested Pareto Set Learning
ProtoVAR: Efficient Dataset Distillation via Prototype-Guided Visual Autoregressive Modeling
FreeRet: MLLMs as Training-Free Retrievers
ForceForget: Reinforcement Concept Removal for Enhancing Safety in Text-to-Image Models
Towards Cold-Start Drafting and Continual Refining: A Value-Driven Memory Approach with Application to NPU Kernel Synthesis
A3: an Analytical Low-Rank Approximation Framework for Attention
Rooted Absorbed Prefix Trajectory Balance with Submodular Replay for GFlowNet Training
Loss-aware distributionally robust optimization via trainable optimal transport ambiguity sets
Rethinking Forgery Attacks on Semantic Watermarks in Black-Box Settings: A Geometric Distortion Perspective
Equivalence of Context and Parameter Updates in Modern Transformer Blocks
Cheap2Rich: A Multi-Fidelity Framework for Data Assimilation and System Identification of Multiscale Physics - Rotating Detonation Engines
TIMI: Training-Free Image-to-3D Multi-Instance Generation with Spatial Fidelity
Proact-VL: A Proactive VideoLLM for Real-Time AI Companions
DynaMem: Consistent Long Video Generation via Hierarchical Memory and Motion Priors
“Do Diffusion Models Dream of Electric Planes?” Discrete and Continuous Simulation-Based Inference for Aircraft Design
Can We Build a Monolithic Model for Fake Image Detection? SICA: Semantic-Induced Constrained Adaptation for Unified-Yet-Discriminative Artifact Feature Space Reconstruction
Faithful Relational Reasoning with Region-based Embeddings: Expressivity of Convex Coordinate-wise Models
STRIDE: Post-Training LLMs to Reason and Refine Bio-Sequences via Edit Trajectories
Benchmarking and Evolving Reason-Reflect-Rectify for Reflective Visual Generation
The Geometry of Representational Failures in Vision Language Models
From Interactions to Principles: Experience-Driven Self-Distillation for Evolving LLM Agents
OPUS: Towards Efficient and Principled Data Selection in Large Language Model Pre-training in Every Iteration
Discovering Ordinary Differential Equations with LLM-Based Qualitative and Quantitative Evaluation
Semi-Supervised Gaze Estimation via Disentangled Subspace Contrastive Learning
Uncovering Bias Mechanisms in Observational Studies
RACER: Risk-Aware Calibrated Efficient Routing for Large Language Models
Unlearning Isn't Deletion: Investigating Reversibility of Machine Unlearning in LLMs
TransLight: Image-Guided Customized Lighting Control with Generative Decoupling
FOAM: Frequency and Operator-Error Based Adaptive Damping Method for Reducing Staleness-Oriented Error for Shampoo
AgentTailor: A Semantic-Aware LLM-Based Multi-Agent System with Actor-Critic Structure
DAL: A Practical Prior-Free Black-Box Framework for Piecewise Stationary Bandits
Delving into Non-Exchangeability for Conformal Prediction in Graph-Structured Multivariate Time Series
3D-DLP: Self-supervised 3D Object-centric Scene Representation Learning
Learning Graph Foundation Models on Riemannian Graph-of-Graphs
Proximal-Based Generative Modeling for Bayesian Inverse Problems
Debiased Model-based Representations for Sample-efficient Continuous Control
A Constrained Optimization Perspective of Unrolled Transformers
How to Train Your Advisor: Steering Black-Box LLMs with Advisor Models
RL with Learnable Textual Feedback: A Bilevel Approach
Plain Transformers are Surprisingly Powerful Link Predictors
Provably Label-Efficient Conformal Prediction
A hitchhiker's guide to Poisson gradient estimation
MulFCoder: Framework-conditioned Multi-agent for MLLM-based Multi-framework Front-end Code Generation
Escaping Whack-a-Mole: Optimizing Documentation as Repo-Specific Playbooks for Coding Agents
Is Vibe Coding Safe? Benchmarking Vulnerability of Agent-Generated Code in Real-World Tasks
Bandit Social Leaning Dynamics with Exploration Episodes
Large Language Model Teaches Visual Students: Cross-Modality Transfer of Fine-Grained Conceptual Knowledge
InteractBench: Benchmarking LLMs on Competitive Programming under Unrevealed Information
Escaping the Likelihood Trap: Geometric Diversity Optimization for Long-Form Image Captioning
BEST: Benchmarking Efficiency in Space and Time for LLM-Generated Code
STORM: Segment, Track, and Object Re-Localization from a Single Image
SGERA: Stein-Guided ECG-Report Alignment for ECG Representation Learning
GEM-FI: Gated Evidential Mixtures with Fisher Modulation
Dimensionality Reduction with Point-distributions Similarity Invariant
Learning Unmasking Policies for Diffusion Language Models
GLEAN: Guideline-Grounded Evidence Accumulation for High-Stakes Agent Verification
Forget-It-All: Multi-Concept Machine Unlearning via Concept-Aware Neuron Masking
PPT-Eval: A Benchmark for Computer-Use Agents on PowerPoint Tasks
Mobility-Embedded POIs: Learning What A Place Is and How It Is Used from Human Movement
RLAnything: Forge Environment, Policy, and Reward Model in Completely Dynamic RL System
Parameter-Masked Decoupled Optimization for Cross-Domain Class-Incremental Learning
Keeping a Secret Requires a Good Memory: Space Lower-Bounds for Private Algorithms
FIRE: Multi-fidelity Regression with Distribution-conditioned In-context Learning using Tabular Foundation Models
Riemannian Metric Matching for Scalable Geometric Modeling of Distributions
Understanding Catastrophic Forgetting In LoRA via Mean-Field Attention Dynamics
MOOSE-Star: Unlocking Tractable Training for Scientific Discovery by Breaking the Complexity Barrier
L-Drive: Beyond a Single Mapping—Latent Context Drives Time Series Forecasting
Ratio-Variance Regularized Policy Optimization
KBQA-R1: Reinforcing Large Language Models for Knowledge Base Question Answering
Goal-Oriented Lower-Tail Calibration of Gaussian Processes for Bayesian Optimization
Convex Optimization for Alignment and Preference Learning on a Single GPU
SLAT: Segment-Level Adaptive Trimming for Efficient CoT Reasoning
Two-Stage Unit Tying for Simplifying Differentiable Logic Gate Networks
Toward Stable Value Alignment: Introducing Independent Modules for Consistent Value Guidance
Stochastic Minimum-Cost Reach-Avoid Reinforcement Learning
Multi-Round Human–AI Collaboration with User-Specified Requirements
On the Difficulty of Learning a Meta-network for Training Data Selection
The Truth Lies Somewhere in the Middle (of the Generated Tokens)
Sparse Regression with $\ell_0$ Constraints for $\alpha$-Mixing Time Series: Algorithms and Guarantees
Equilibrium Pricing in Oligopolistic Data Markets
On the Interplay of Pre-Training, Mid-Training, and RL on Reasoning Language Models
3DMedAgent: Unified Perception-to-Understanding for 3D Medical Analysis
D-FUSEr: Diverse Failure, Unified Success via Error-Distribution Shaping in LLM Reasoning
Class-Conditional Distribution Balancing for Group Robust Classification
Local Policies for Graph-Structured Markov Decision Processes
Rashomon Sets of Falling Trees
DF-ExpEnse: Diffusion Filtered Exploration for Sample Efficient Finetuning
Self-correcting for Debiasing Large Language Models
Compressed Sensing for Capability Localization in Large Language Models
Procedural Pretraining: Warming Up Language Models with Abstract Data
Functional Adjoint Sampler: Scalable Sampling on Infinite Dimensional Spaces
$f$-Divergence Regularized RLHF: Two Tales of Sampling and Unified Analyses
Reflex: Real-Time Vision-Language-Action Control through Streaming Inference
Per-example Gradients: a New Frontier for Understanding and Improving Optimizers
Learning Treatment Representations for Downstream Instrumental Variable Regression
Active Timepoint Selection for Learning Measure-Valued Trajectories
Clipping Bottleneck: Stabilizing RLVR via Stochastic Recovery of Near-Boundary Signals
Think Fast and Slow: Step-Level Cognitive Depth Adaptation for LLM Agents
Principled Confidence Estimation for Deep Computed Tomography
Quantifying Cross-Domain Knowledge Distillation in the Presence of Domain Shift
Foundations of Equivariant Deep Learning: Unifying Graph and Sheaf Neural Networks
Evolutionary Multi-View Classification with Label Noise via Gradient and Feature Dual-Perception
DELTA4: Sparse Matrix-Vector Multiplication for Low Sparsity
Language Model Augmented Semi-Supervised Statistical Inference
Smooth Multi-Policy Causal Effect Estimation in Longitudinal Settings
DisjunctiveNet: Neural Symbolic Learning via Differentiable Convexified Optimization Layers
Certifying Capabilities from Finite Tests: When Is It Possible?
MASH: Modeling Abstention via Selective Help-Seeking
Learning Unanimously Acceptable Lotteries via Queries
When to Trust the Cheap Check: Weak and Strong Verification for Reasoning
Fantastic Reasoning Behaviors and Where to Find Them: Unsupervised Discovery of the Reasoning Process
Signature-Informed Transformer for Asset Allocation
From Moments to Models: Graphon-Mixture Learning for Mixup and Contrastive Learning
An Exponential Separation Between Quantum and Quantum-Inspired Classical Algorithms for Linear Systems
Scaling Small Agents Through Strategy Auctions
Scaling Laws of Global Weather Models
OLion: Approaching the Hadamard Ideal by Intersecting Spectral and L inf Implicit Biases
Correcting Split Selection in Online Decision Trees via Anytime-Valid Inference
Why Dedicated Critics: Eliminating Target Drift in Multi-Constraint RL
Privacy-Aware Video Anomaly Detection: Guided Orthogonal Projection and a Comprehensive Evaluation Framework
Differentiable Weightless Controllers: Learning Logic Circuits for Continuous Control
Sponge Tool Attack: Stealthy Denial-of-Efficiency against Tool-Augmented Agentic Reasoning
Global Geometry Is Not Enough for Vision Representations
LakeQA: An Exploratory QA Benchmark over a Million-Scale Data Lake
Many Experiments, Few Repetitions, Unpaired Data, and Sparse Effects: Is Causal Inference Possible?
Privately Fine-Tuned LLMs Preserve Temporal Dynamics in Tabular Data
SpecMD: A Comprehensive Study On Speculative Expert Prefetching
A Random Matrix Perspective on the Consistency of Diffusion Models
DPO Unchained: Your Training Algorithm is Secretly Disentangled in Human Choice Theory (and Its Loss' Convexity is Dispensable)
Protein Fold Classification at Scale: Benchmarking and Pretraining
The Decrypto Benchmark for Multi-Agent Reasoning and Theory of Mind
VSCD: Video-based Scene Change Detection in Unaligned Scenes
Unveiling the Role of Data Uncertainty in Tabular Deep Learning
Disentangling Geometry, Performance, and Training in Language Models
Torus Graphs for Large Scale Neural Phase Analysis
DDSVM: A Differentiable Framework for Deep Support Vector Machines with Iterative Geometry-Aware Optimization
Fair Classification with Efficient and Post-hoc Controllable Fairness-Accuracy Trade-off
dgMARK: Decoding-Guided Watermarking for Diffusion Language Models
Skewness-Robust Causal Discovery in Location-Scale Noise Models
Excited Pfaffians: Generalized Neural Wave Functions Across Structure and State
OOVDet: Low-Density Prior Learning for Zero-Shot Out-of-Vocabulary Object Detection
Revenue Efficiency of Correlated Equilibria in First Price Auctions
HiPPO Zoo: Explicit Memory Mechanisms for Interpretable State Space Models
Dual Quaternion SE(3) Synchronization with Recovery Guarantees
Discriminative Attribute Graph Clustering Through Topology-Guided Contrastive Learning
Post-Training with Policy Gradients: Optimality and the Base Model Barrier
Beyond Correctness: Distance-Based Social Dynamics of Multi-Agent Debate
Semantic Granularity Navigation in Image Editing
ScaleMoE: Mixture-of-Experts for Scalable Continuous Control in Actor-Critic Reinforcement Learning
Every Step Counts: Decoding Trajectories as Authorship Fingerprints of dLLMs
LLM Priors for ERM over Programs
Self-Distillation Enables Continual Learning
Collaborative Learning for Semi-Supervised LiDAR Semantic Segmentation
Diversity-Aware Recursive Feature Multiple Kernel Learning
ConFlux: Multivariate Time Series in Flux, One Unified Forecast in Confluence
IsoCompute Playbook: Optimally Scaling Sampling Compute for LLM RL
Latent Collaboration in Multi-Agent Systems
Improving the Performance and Learning Stability of Parallelizable RNNs Designed for Ultra-Low Power Applications
From Backward Spreading to Forward Replay: Revisiting Target Construction in LLM Parameter Editing
Spectra: Rethinking Optimizers for LLMs Under Spectral Anisotropy
Chain-of-Thought Gradient Descent
Hallucination is a Consequence of Space-Optimality: A Rate-Distortion Theorem for Membership Testing
Grounding Multi-Hop Reasoning in Structural Causal Models via Group Relative Policy Optimization
Tightening the Score Matching Gap for Diffusion Models
FRIGID: Scaling Diffusion-Based Molecular Generation from Mass Spectra at Training and Inference Time
CoFrGeNet: Continued Fraction Architectures for Language Generation
Safe and Scalable Web Agent Learning via Recreated Websites
Open Materials Generation with Inference-Time Reinforcement Learning
On Regret Bounds of Thompson Sampling for Bayesian Optimization
Do We Need Adam? Surprisingly Strong and Sparse Reinforcement Learning with SGD in LLMs
FlashSketch: Sketch-Kernel Co-Design for Fast Sparse Sketching on GPUs
Scaling Law for Quantization-Aware Training
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