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What Characterizes Effective Reasoning? Revisiting Length, Review, and Structure of CoT
SAQNN: Spectral Adaptive Quantum Neural Network as a Universal Approximator
Near-Optimal Regret for KL-Regularized Multi-Armed Bandits
SCRWKV: Ultra-Compact Structure-Calibrated Vision-RWKV for Topological Crack Segmentation
Continuous Variable Hamiltonian Learning at Heisenberg Limit via Displacement-Random Unitary Transformation
Rethinking Neural Network Learning Rates: A Stackelberg Perspective
SpikeNet: Sparse Spike-Driven Mask Vector Transformer for Energy-Efficient and Stable Spiking Point Cloud Processing
FOAM: Frequency and Operator-Error Based Adaptive Damping Method for Reducing Staleness-Oriented Error for Shampoo
Flat Minima and Generalization: Insights from Stochastic Convex Optimization
Hyper-ICL: Attention Calibration with Hyperbolic Anchor Distillation for Multimodal In-Context Learning
Persona-Pruner: Sculpting Lightweight Models for Role-Playing
Von Mises-Fisher Mixture Model with Dynamic Shrinkage for Realistic Test-Time Transduction
Data Augmentation of Contrastive Learning is Estimating Positive-incentive Noise
DLO-Lab: Benchmarking Deformable Linear Object Manipulations with Differentiable Physics
QPoint: End-to-End Lightweight Point Cloud Processing via Robust Quaternion Feature Learning
VERA-V: Variational Inference Framework for Jailbreaking Vision-Language Models
Reliability-Aware LLM Alignment from Inconsistent Human Feedback
Geometry-based Schrödinger Bridges for Trustworthy Multimodal Fusion
Precise Asymptotics of Bagging Regularized M-estimators
An Algebraic View of the Expressivity of Recurrent Language Models
Length Generalization Bounds for Transformers
Adaptive Batch Sizes Using Non-Euclidean Gradient Noise Scales for Stochastic Sign and Spectral Descent
ManiSoft: Towards Vision-Language Manipulation for Soft Robotics
Learn to Merge: Meta-Learning for Adaptive Multi-Task Model Merging
History-Bootstrapped Flow Matching for Inverse Boiling Reconstruction
Entropy-Aware On-Policy Distillation of Language Models
Causal Effect Identifiability in the Presence of Latent Confounders Without Auxiliary Variables
Outcome-Aware Spectral Feature Learning for Instrumental Variable Regression
Unlocking Noise-Resistant Vision: Key Architectural Secrets for Robust Models Against Gaussian Noise
Learning General Causal Structures with Hidden Dynamic Process for Climate Analysis
Regret-Based Federated Causal Discovery with Unknown Interventions
CauScale: Neural Causal Discovery at Scale
Differentially Private Submodular Maximization with a Knapsack Constraint
Towards Completeness in Causal Discovery from Soft Interventions with Known Targets
What Does Preference Learning Recover from Pairwise Comparison Data?
Rethinking Visual Autoregressive Sampling with Information-Grounding Guidance
Frequentist Consistency of Prior-Data Fitted Networks for Causal Estimation
Rethinking Visual Intelligence: Insights from Video Pretraining
FedTreeLoRA: Reconciling Statistical and Functional Heterogeneity in Federated LoRA Fine-Tuning
Partial Identification under High-Dimensional Potential Outcomes and Confounders via Optimal Transport
Causal Discovery for Irregularly Time Series with Consistency Guarantees
CAffNet: Hard Constraint-Affine Neural Networks
effGen: Enabling Small Language Models as Capable Autonomous Agents
The Generalization Spectrum: A Chromatographic Approach to Evaluating Learning Algorithms
Optimal Bayesian Stopping for Efficient Inference of Consistent LLM Answers
CausalGame: Benchmarking Causal Thinking of LLM Agents in Games
Trajectory-Aware Heuristic Learning for Combinatorial Search
Evaluating Agentic Optimization on Large Codebases
Magnitude Distance: A Geometric Measure of Dataset Similarity
ASyMOB: Algebraic Symbolic Mathematical Operations Benchmark
The Abstraction Gap in Vision-Language Causal Reasoning
Operationalizing the Superficial Alignment Hypothesis via Task Complexity
ASTRA: Communication-Efficient Acceleration for Multi-Device Transformer Inference
Pretrained Vision-Language-Action Models are Surprisingly Resistant to Forgetting in Continual Learning
Learning Situated Awareness in the Real World
From Shortcuts to Reasoning: Robust Post-Training of Theory of Mind with Reinforcement Learning
Revisiting Neural Processes via Fourier Transform and Volterra Series
Multi-Distribution Robust Conformal Prediction
MultiBreak: A Scalable and Diverse Multi-turn Jailbreak Benchmark for Evaluating LLM Safety
A Foundation-style Model for Zero-Shot Statistical Dependency Measurement
RQ-MoE: Residual Quantization via Mixture of Experts for Efficient Input-Dependent Vector Compression
Verifying Meta-Awareness via Predictive Rewards in Reasoning Models
pTNAS: Progressive Neural Architecture Search for Tabular Data
CooT: Learning to Coordinate In-Context with Coordination Transformers
Trust Functions: Near Lossless Weak-to-Strong Generalization by Learning to Trust the Weak Teacher
Beyond Accuracy and Complexity: The Effective Information Criterion for Structurally Stable Symbolic Regression
Learning Flexible Generalization in Video Quality Assessment by Bringing Device and Viewing Condition Distributions
When Softmax Fails at the Top: Extreme‑Value Corrections for InfoNCE
Recognize Your Orchestrator: An Entropy Dynamics Perspective for LLM Multi-Agent Systems
Test-Time Learning of Causal Structure from Interventional Data
DIYHealth Suite: Dataset, Model, and Benchmark for Health Management at Home
Breaking the Lock-in: Diversifying Text-to-Image Generation via Representation Modulation
TIME: Tensor-Factorized Mixture-of-Experts with Intrinsic Routing for Lifelong Multimodal Knowledge Editing
Beyond Prediction: Tail-Aware Scheduling for LLM Inference
Learning to Rank by Directly Optimizing Full-Order Probabilities
FedReLa: Imbalanced Federated Learning via Re-Labeling
Fast Autoregressive Video Diffusion and World Models with Temporal Cache Compression and Sparse Attention
Symbiosis-Inspired Knowledge Distillation for Incremental Object Detection
Component-Wise Composite Likelihood Distillation for Censored Time-to-Event Data
StarEmbed: Benchmarking Time Series Foundation Models on Astronomical Observations of Variable Stars
Merge to Remember: Sharpness-Aware Isotropic Merging for Continual Learning
OBJVanish: Prompt-Driven Generation of Physically Realizable 3D LiDAR-Invisible Objects
Rethinking the Hardness of PbRL: A Provable General Regret Bound
Low-dimensional topology of deep neural networks
Fine-Tune Once, Reuse Across Models: Bayesian Task-Update Factors and Approximations
Outcome-Based Rewards Do Not Guarantee Faithful and Verifiable Reasoning
ImgCoT: Compressing Long Chain of Thought into Compact Visual Tokens for Efficient Reasoning of Large Language Model
From Lyapunov Analysis to Algorithm Design in two-sided PL Minimax Optimization
Lightweight and Interpretable Transformer via Unrolling of Mixed Graph Algorithms for Traffic Forecast
Improving Neural Topic Modeling with Semantically-Grounded Soft Label Distributions
Social Hippocampus Memory Learning
DISSOLVR: An Interpretable and Fast Framework for Aqueous and Organic Solubility Prediction
TranX-Adapter: Bridging Artifacts and Semantics within MLLMs for Robust AI-generated Image Detection
Lower Bounds for Frank-Wolfe on Strongly Convex Sets
Adaptive Momentum and Nonlinear Damping for Neural Network Training
DTS: Enhancing Large Reasoning Models via Decoding Tree Sketching
Online Learning and Inference for Cox Proportional Hazards Model Using Renewable Sieve Estimation
Learning Self-Interpretation from Interpretability Artifacts: Training Lightweight Adapters on Vector-Label Pairs
(Sparse) Attention to the Details: Preserving Spectral Fidelity in ML-based Weather Forecasting Models
Aligning Tree-Search Policies with Fixed Token Budgets in Test-Time Scaling of LLMs
DIVA: Harnessing the Representation Divergence in Unified Multimodal Models for Mutual Reinforcement
Artemis: Structured Visual Reasoning for Perception Policy Learning
Adaptive Contracts for Cost-Effective AI Delegation
Benchmarking Dense and Indiscernible Object Counting with Blueberries
Design Linear Constrained Neural Layers with Implicit Convex Optimization
Evaluating Object-Centric Models beyond Object Discovery
From Basis to Basis: Gaussian Particle Representation for Interpretable PDE Operators
Optimal Transport–Guided Stochastic Control for Graph Combinatorial Optimization
Simple Unbiased Derivative Free Inference-Time Scaling for Diffusion Models via Sequential Monte Carlo on Path Measures
Bottleneck Communication Delay Minimization for Communication-Efficient Decentralized Learning
Ambiguous Strategic Classification
HO-SFL: Hybrid-Order Split Federated Learning with Backprop-Free Clients and Dimension-Free Aggregation
CoDA-Bench: Can Code Agents Handle Data-Intensive Tasks?
Flowers: A Warp Drive for Neural PDE Solvers
Row-stochastic matrices can provably outperform doubly stochastic matrices in decentralized learning
Let EEG Models Learn EEG
Divide and Learn: Multi-Objective Combinatorial Optimization at Scale
Complexity of Decentralized Optimization with Mixed Affine Constraints
Temporal Difference Calibration in Sequential Tasks: Application to Vision-Language-Action Models
RuCL: Stratified Rubric-Based Curriculum Learning for Multimodal Large Language Model Reasoning
FACT: Fuzzy Alignment with Comorbidity Topology for Reliable Multi-Label Medical Image Diagnosis
EPSVec: Efficient and Private Synthetic Text Generation via Dataset Vectors
Multi-Task GRPO: Reliable LLM Reasoning Across Tasks
Evidential Reasoning Advances Interpretable Real-World Disease Screening
PhyScene3D: Physically Consistent 3D Interactive Tabletop Scene Generation
TabICooL: A better, faster, scalable, and open tabular foundation model
FAB: A First-Order AB-based Gradient Algorithm for Distributed Bilevel Optimization over Time-Varying Directed Graphs
A Tight Theory of Error Feedback Algorithms in Distributed Optimization
It's a TRAP! Task-Redirecting Agent Persuasion Benchmark for Web Agents
Transformers Provably Learn Algorithmic Solutions for Graph Connectivity, But Only with the Right Data
Training with Honeypots: Reshaping How LLMs Fail
FedCDWA: Decoupled Federated Prototype Distillation with Hierarchical Wasserstein Aggregation
Robust Federated Learning Against Adaptive Compression
Recurrent Equivariant Constraint Modulation: Learning Per-Layer Symmetry Relaxation from Data
GHOST: Unmasking Phantom States in Mamba2 via Grouped Hidden-state Output-aware Selection & Truncation
On the Role of Batch Size in Stochastic Conditional Gradient Methods
MESA: Improving MoE Safety Alignment via Decentralized Expertise
From Muon to Gluon: Bridging Theory and Practice of LMO-based Optimizers for LLMs
TextME: Bridging Unseen Modalities Through Text Descriptions
Stability beyond bounded differences: sharp generalization bounds under finite $L_p$ moments
From Representation to Action: A Unified Laplacian Framework for Spatial Representation and Path Planning
NaviCache: Test-Time Self-Calibration Caching for Video Generation
Latent Thoughts Tuning: Bridging Context and Reasoning with Fused Information in Latent Tokens
Private Learning with Public Feature Conditioning
Rethinking Code Complexity Through the Lens of Large Language Models
Decision-focused Sparse Tangent Portfolio Optimization
Beyond the Bellman Recursion: A Pontryagin-Guided Framework for Non-Exponential Discounting
Unlocking Speech–Text Compositional Powers: Instruction-Following Speech Language Models without Instruction Tuning
Learning Dynamics of Zeroth-Order Optimization: A Kernel Perspective
Constructing Industrial-Scale Optimization Modeling Benchmark
BEDTime: A Unified Benchmark for Automatically Describing Time Series
Intrinsic Credit Assignment for Long Horizon Interaction
Federated Graph Learning via Structure-Aware Fusion Using a Kalman Framework with Learnable Dynamics
XTransfer: Modality-Agnostic Few-Shot Model Transfer for Human Sensing at the Edge
Adapting to Evolving Graphs: A Scalable Framework for Dynamic Coarsening
Spherical SO(3) Equivariant Local Attention
AdaMEM: Test-Time Adaptive Memory for Language Agents
Taming I2V models for Image HOI Editing: A Cognitive Benchmark and Agentic Self-Correcting Framework
SoftBinary Coding: A New Information-Theoretic Paradigm for Neural Compression via Fast Channel Simulation
Minibatch selection for Language Models via Partition Matroid Constrained Gradient Matching
Strategy-Aware Optimization Modeling with Reasoning LLMs
Noisy-Channel Minimum Bayes Risk Decoding
SPEED-Bench: A Unified and Diverse Benchmark for Speculative Decoding
Latent Guided Sampling for Combinatorial Optimization
Tuning the Implicit Regularizer of Masked Diffusion Language Models: Enhancing Generalization via Insights from $k$-Parity
Testing For Distribution Shifts with Conditional Conformal Test Martingales
An Efficient Joint Learning Approach for Item Response Theory
Interleaved Selective State Space Models for Efficient WiFi-Based 3D Multi-Person Pose Estimation
AutoRPA: Efficient GUI Automation through LLM-Driven Code Synthesis from Interactions
From Similarity to Vulnerability: Key Collision Attack on LLM Semantic Caching
Expectation Consistency Loss: Rethink Confidence Calibration under Covariate Shift
Extending Prediction-Powered Inference through Conformal Prediction
Position: Genomic Model Research Must Move Beyond Anecdotal Evaluation of Interpretability Methods
T-POP: Test-Time Personalization with Online Preference Feedback
Beyond Fixed Biases: Decoding the Role of Reasoning Uncertainty in MLLM Modality Conflicts
Probability of Matching for Batch Multi-Objective Bayesian Optimization
Localizing Memorized Regions in Diffusion Models via Coordinate-Wise Curvature Differences
Proximal Decoding: Provably Reducing Copyright Risk for Any Language Model
DB-KSVD: Scalable Alternating Optimization for Disentangling High-Dimensional Embedding Spaces
GeoSense: Internalizing Geometric Necessity Perception for Multimodal Reasoning
Explanations are a Means to an End: A Value of Information Framework for Validating Explanations
SMILE: Extended Deep Submodular Function-Based Instruction and In-context Learning Demonstration Selection
Long Live The Balance: Information Bottleneck Driven Tree-based Policy Optimization
Position: The Privacy-Auditability Paradox in Federated Learning: Why We Need Controllable Secure Aggregation
Beyond the Trade-off: Unifying Fairness and Performance in Federated Learning
Knowing When to Quit: A Principled Framework for Dynamic Abstention in LLM Reasoning
Accurate, private, secure, federated U-statistics with higher degree
A Factorized Low-Rank RNN Framework for Uncovering Independent Neural Latent Dynamics and Connectivity
A Studentized Spherical Harmonics–Based Nonparametric Two-Sample Test for Compositional and Directional Data
SlaClip: Gradient Norm Slacks can be Indicator for Adaptive Clipping in DP-SGD
Formalizing and Falsifying Causal Pathways of Rare Events
An Empirical Study on the Resilience of Partial Merging to Model Clone Attacks
Beyond Sample-Level Forgetting: Improving Reliability in Multimodal Unlearning
PsumQuant: In-line Post-training Partial Sum Quantizer for Energy Efficient NPU Inference
Discovering Interpretable Algorithms by Decompiling Transformers to RASP
Revisiting ML Training under Fully Homomorphic Encryption: Convergence Guarantees, Differential Privacy, and Efficient Algorithms
WhisperSplat: Lossless Steganography in 3D Gaussian Splatting
Differentially Private Range Subgraph Counting
Gradient Flow Sampler-based Distributionally Robust Optimization
Enhancing Membership Inference Attacks on Diffusion Models from a Frequency-Domain Perspective
Differentially Private Cross-Silo Recommendation from Implicit Feedback
Gradient Inversion Attacks Beyond SGD
User-Aware Active Knowledge Acquisition for Emotional Support Dialogue
Differentially Private Synthetic Tabular Data via Private Evolution
Forward-KL Convergence of Time-Inhomogeneous Langevin Diffusions
Full-Batch Gradient Descent Outperforms One-Pass SGD: Sample Complexity Separation in Single-Index Learning
Precision-Induced Miscalibration: Understanding and Correcting Confidence Distortion in Quantized Neural Networks
DP-KFC: Data-Free Preconditioning for Privacy-Preserving Deep Learning
LS$^{2}$MC-GDA: A Smoothed Algorithm for Federated Stochastic Compositional Minimax Optimization
Differentially Private Geodesic Regression
Exact and Approximate Algorithms for Polytree Learning
Layer-Centric Factors of Variation Disentanglement for Task- and Model-Agnostic Generalization
Lookahead Sample Reward Guidance for Test-Time Scaling of Diffusion Models
Coverage, Not Averages: Semantic Stratification for Trustworthy Retrieval Evaluation
PrivGate: Steering Contextual Integrity in LLMs via Latent Space Geometry
Detecting the Semantic Fixed Point: A Geometric Framework for Efficient Inference
The Hidden Risk: Membership Inference Attacks on Multimodal Federated Learning via Modality Imbalance
Maximizing mutual information between prompt and response improves LLM performance with no additional data
Distilling Neuro-Symbolic Programs into 3D Multi-modal LLMs
The Forgetting-Retention Dilemma: Certified Unlearning Theory in Continual Learning
Continuous Viewpoint Adaptation for Single View 3D Object Reconstruction
Stochastic Gradient Methods under Heavy-Tailed Noises in Weakly Convex Optimization
Towards Seed-Robust Safety Alignment in Text-to-Image Models
Path-Coupled Bellman Flows for Distributional Reinforcement Learning
Multimodal Latent Language Modeling with Next-Token Diffusion
Safety Anchor: Defending Harmful Fine-tuning via Geometric Bottlenecks
Does AI Reviewer See the Full Picture? Attacking and Defending Multimodal Peer Review
From Inpainting to Editing: Unlocking Robust Mask-Free Visual Dubbing via Generative Bootstrapping
MusicDET: Zero-Shot AI-Generated Music Detection
Can Computational Reducibility Lead to Transferable Models for Graph Combinatorial Optimization?
Same Graph Cross-Task Transfer in GNNs: Protocols and Predictors
Think Deep, Not Just Long: Measuring LLM Reasoning Effort via Deep-Thinking Tokens
SCOPE: Evolving Symbolic World for Planning in Open-Ended Environments
TimeGuard: Channel-wise Pool Training for Backdoor Defense in Time Series Forecasting
BARRED: Synthetic Training of Custom Policy Guardrails via Asymmetric Debate
Local Redundancy: An Information-Theoretic Measure of Plasticity from Synthetic Memorization
ICR-RL: Deep Reinforcement Learning via In-Context-Regression
Kuramoto Oscillatory Phase Encoding: Neuro-inspired Synchronization for Improved Learning Efficiency
MedScope: Incentivizing "Think with Videos" for Clinical Reasoning via Coarse-to-Fine Tool Calling
Convergence Analysis of Decentralized Hessian-/Jacobian-Free Algorithm for Nonconvex Stochastic Bilevel Optimization
Understanding Data Temporality Impact on Large Language Models Pre-training
SABER: Continual Learning with Representation Conflict Management
Identifying Common Hubs in Multiple Gaussian Graphical Models
Hair-Trigger Alignment: Black-Box Evaluation Cannot Guarantee Post-Update Alignment
Designing Observation and Action Models for Efficient Reinforcement Learning with LLMs
Embedding Trust: Semantic Isotropy Predicts Nonfactuality in Long-Form Text Generation
Signal Strength Estimation in Logistic Regression Using Data Splitting
FlashBlock: Attention Caching for Efficient Long-Context Block Diffusion
Non-Uniform Noise-to-Signal Ratio in the REINFORCE Policy-Gradient Estimator
Selective Disclosure Watermarking for Large Language Models
VPD-100K: Towards Generalizable and Fine-grained Visual Privacy Protection
DisPOSE: Projected Polystochastic Diffusion for Self-Supervised Multi-View 3D Human Pose Estimation
Front-Loaded Robust Conformal Prediction: Heavy Calibration, Minimal Test-Time Cost
StructMamPose: From Sequential Perception to Structural Reasoning for 3D Human Pose Estimation
Attention with Routed-Memory for Learnable Sparse Control
Not All Answers Are Contextually Persuadable: Inference Dynamics in Large Language Models under Contextual Influence
Semantic Robustness Certification for Vision-Language Models
Approximation Bounds for Transformer Networks with Application to Regression
Scalable Medical Multimodal Fusion via Symmetric Consistency Modeling
Attention Sink Forges Native MoE in Attention Layers: Sink-Aware Training to Address Head Collapse
Context Distillation Retains Post-Training Capabilities in Continually Trained LMs
Q-Delta: Beyond Key–Value Associative State Evolution
MDN: Parallelizing Stepwise Momentum for Delta Linear Attention
Explainable Forensics of Manipulated Segments in Untrimmed Long Videos
Poison with Style: A Practical Poisoning Attack on Code Large Language Models
Preconditioned DeltaNet: Curvature-aware Sequence Modeling for Linear Recurrences
Rethinking 3D Shape Generation: Diffusion over Superquadrics
FiX: Introducing Fine-grained Forget Gate into Softmax Attention
ThoughtFold: Folding Reasoning Chains via Introspective Preference Learning
RAT+: Train Dense, Infer Sparse - Recurrence Augmented Attention for Dilated Inference
Video-SVD: Efficient Video Diffusion via Orthogonal Basis Composition
ParalESN: Enabling parallel information processing in Reservoir Computing
Emergence of Exploration in Policy Gradient Reinforcement Learning via Retrying
TileSparse: Arithmetic-Intensity-Aware Sparse Attention for Compute-Bound LLM Decoding
RSPO: Regularized Self-Play Alignment of Large Language Models
Betting on Predictions
scDataset: Scalable Data Loading for Deep Learning on Large-Scale Single-Cell Omics
Possibilistic Predictive Uncertainty for Deep Learning
Learning Useful Supervision for Reinforcement Learning in Reasoning Models
Can LLMs Reason Like Automated Theorem Provers for Rust Verification? VCoT-Bench: Evaluating via Verification Chain of Thought
Knowledge Diversion for Efficient Morphology Control and Policy Transfer
Calibrated Test-Time Guidance for Bayesian Inference
Faster Than Flash: Exploiting Attention Sparsity for Efficient Long-Context Decoding
EchoAttention: Exploiting Token-Pair Redundancy and Frame-Block Similarity for Efficient Long Video Generation
DiffuReason: Enhancing Reasoning Ability for Diffusion Language Models via Monte Carlo Tree Search
Overcoming the Modality Gap in Context-Aided Forecasting
Causal Fine-Tuning under Latent Confounded Shift
Can Microcanonical Langevin Dynamics Leverage Mini-Batch Gradient Noise?
When Can You Poison Rewards? A Tight Characterization of Reward Poisoning in Linear MDPs
Teaching Agents to Ask Effective Clarification Questions
MatchFixAgent: Language-Agnostic Autonomous Repository-Level Code Translation Validation and Repair
Mesh Field Theory: Port–Hamiltonian Formulation of Mesh-Based Physics
RePack then Refine: Efficient Diffusion Transformers with Vision Foundation Models
CGRiC: Compositional Risk Certification for Structured LLM Outputs
KANFIS: A Neuro-Symbolic Framework for Interpretable and Uncertainty-Aware Learning
Training-Free Adversarial Robustness in Deep Learning MRI Reconstruction
Position: It is Time to Virtualize Foundation Models with a Self-evolving Operating System Layer
Position: When AI Decides Who Gets an Organ: Multi-Agentic AI Systems in Transplant Medicine Risk Amplifying Disparities Without Targeted Explainability and Deployment Strategies
Self-Supervised Weight Templates for Scalable Vision Model Initialization
OnePO: Direct One-stage Policy Optimization for SFT-free Domain Adaptation
Diffusion differentiable resampling
Iterative Robust Satisficing: Minimizing Performance Degradation Under Distribution Shift
Graph is a Substrate Across Data Modalities
Saliency-Aware Model Merging
DTop-p MoE: Sparsity-Controlled Dynamic Top-p MoE for Foundation Model Pre-training
No Need to Train Your RDB Foundation Model
Relational In-Context Learning via Synthetic Pre-training with Structural Prior
PINE: Pruning Boosted Tree Ensembles with Conformal In-Distribution Prediction Equivalence
PluRel: Synthetic Data unlocks Scaling Laws for Relational Foundation Models
Alethia: a Foundational Encoder for Voice Deepfakes
Attend to Anything: Foundation Model for Unified Human Attention Modeling
Referring Multiple Regions with Large Multimodal Models via Contextual Latent Steering
LoRA-DA: Data-Aware Initialization for Low-Rank Adaptation via Asymptotic Analysis
On the Limits of Test-Time Compute: Sequential Reward Filtering for Better Inference
From Zero to Hero: Advancing Zero-Shot Foundation Models for Tabular Outlier Detection
Copula-SVI: Vine-Copula Variational Inference for Instance-Level Correlation Capturing
Deep Scientific Reasoning under Physical Constraints: Structure-Aware Spectrum Prediction for Electronic Density of States
Towards Unified Multimodal Pretraining
ConceptMoE: Adaptive Token-to-Concept Compression for Implicit Compute Allocation
Stronger Semantic Encoders Can Harm Relighting Performance: A Probe of Visual Priors via Augmented Latent Intrinsics
Exploring and Exploiting Stability in Latent Flow Matching
STABLEVAL: Disagreement-Aware and Stable Evaluation of AI Systems
Distribution Alignment for One-Shot Federated Learning via Optimal Transport
SPEAR: A Unified SSL Framework for Learning Speech and Audio Representations
SWING: Unlocking Implicit Graph Representations for Graph Random Features
Less Diverse, Less Safe: The Indirect But Pervasive Risk of Test-Time Scaling in Large Language Models
Exploration Hacking: LLMs Can Learn to Resist RL Training
LUVE : Latent-Cascaded Ultra-High-Resolution Video Generation with Dual Frequency Experts
Why Tree-Style Branching Matters for Thought Advantage Estimation in GRPO
WS-GRPO: Weakly-Supervised Group-Relative Policy Optimization for Rollout-Efficient Reasoning
video-SALMONN S: Memory-Enhanced Streaming Audio-Visual LLM
One-step Optimal Transport via Regularized Distribution Matching Distillation
On the Ability of Transformers to Verify Plans
OneSearch: A Preliminary Exploration of the Unified End-to-End Generative Framework for E-commerce Search
Combinatorial Sparse PCA Beyond the Spiked Identity Model
DRIVE: Distributional and Retrieval-Augmented Bidding with Value Evaluation
Causal Detection of Multi-Step LLM Agent Attacks
Speech-Audio Compositional Attacks on Multimodal LLMs and Their Defense with SALMONN-Guard
JAEGER: Joint 3D Audio-Visual Grounding and Reasoning in Simulated Physical Environments
3DGS$^2$-TR: A Scalable Second-Order Trust-Region Method for 3D Gaussian Splatting
Logical Guidance for the Exact Composition of Diffusion Models
From Pairwise Affinities to Functional Correspondences: Rethinking Attention
Unveiling the Structure of Do-Calculus Reasoning via Derivation Graphs
LiME: Lightweight Mixture of Experts for Efficient Multimodal Multi-task Learning
A Diffusive Classification Loss for Learning Energy-based Generative Models
One-step Latent-free Image Generation with Pixel Mean Flows
Salus: Strategic Diagnostic Testing for Complex Diagnosis via Multi-Agent Reinforcement Learning
Forward-Chaining Temporal Point Process
Accelerated Dual Method for Distributed Optimization: An Inexact-Gradient View of Local Updates
TadABench-1M: A Large-Scale Wet-Lab Protein Benchmark For Rigorous OOD Evaluation
The Geometry of Sequential Learning: Lie-Bracket Prediction of Transfer Order
DiffCrossGait: Trajectory-Level Alignment for 2D-3D Cross-Modal Gait Recognition via Latent Diffusion
Data-Source Adaptive Online Learning under Heteroscedastic Noise
Local Linearity of LLMs Enables Activation Steering via Model-Based Linear Optimal Control
Diffusion Bridge or Flow Matching? A Unifying Framework and Comparative Analysis
LaTtE-Flow: Layerwise Timestep-Expert Flow-based Transformer
Multimodal Fusion via Self-Consistent Task-Gradient Fields
End-to-End Autoregressive Image Generation with 1D Semantic Tokenizer
Fine-Tuning of Transformer models with Frames
Planar Symmetric Pattern Generation
CausalXRL: Explainable Reinforcement Learning through Causal Graph Reasoning
Meta Flow Maps enable scalable reward alignment
Token Sample Complexity of Attention
Set-Coupled Guidance: Set-Level Coordination in Diffusion-Based Dataset Distillation
Learning Reward Functions from Multiple Feedback Types with Amortized Variational Inference
PICACO: Pluralistic In-Context Value Alignment via Total Correlation Optimization
Selective Coupling of Decoupled Informative Regions: Masked Attention Alignment for Data-Free Quantization of Vision Transformers
Hierarchical Image Tokenization for Multi-Scale Image Super Resolution
ARLArena: Demystifying Policy Gradient Stability in Agentic Reinforcement Learning
MEC: Machine-Learning-Assisted Generalized Entropy Calibration for Semi-Supervised Mean Estimation
Two-dimensional quantization for geometry-aware audio coding
How RL Unlocks the Aha Moment in Geometric Interleaved Reasoning
PPI Candidate Ranking: Large-Scale Evaluation of a Domain Knowledge–Guided Pipeline
Principled Synthetic Data Enables the First Scaling Laws for LLMs in Recommendation
Teaching Molecular Dynamics to a Non-Autoregressive Ionic Transport Predictor
Learning-Augmented Online Minimization with Dual Predictions
Ophiuchus: Incentivizing Tool-augmented ''Think with Images'' for Joint Medical Segmentation, Understanding and Reasoning
Singular Bayesian Neural Networks
Online Change Point Detection for Multivariate Inhomogeneous Poisson Processes Time Series
GIPO: Gaussian Importance Sampling Policy Optimization
Physics-informed diffusion models in spectral space
The Crowded Embedding Space: A Mean-Field Mechanism for Emergent Marginalization in Retrieval-Augmented Agents
SE-GA: Memory-Augmented Self-Evolution for GUI Agents
When Planning Fails Despite Correct Execution: On Epistemic Calibration for LLM-Based Multi-Agent Systems
Turbo Connection: Reasoning as Information Flow from Higher to Lower Layers
FedVeer: Self-Adaptive Skew Estimation for Robust Federated Learning
LECTOR: Joint Learning of Scientific Reasoning Graphs and Introduction Generation
Model-Based Diffusion Sampling for Predictive Control in Offline Decision Making
DSGCR: Decomposed Spectral Geometry-Aware Cross-Modal Semantic Representation for 3D Visual Grounding
Continual Model Routing in Evolving Model Hubs
Solver-in-the-Loop: MDP-Based Benchmarks for Self-Correction and Behavioral Rationality in Operations Research
RedVisor: Reasoning-Aware Prompt Injection Defense via Zero-Copy KV Cache Reuse
Graph-GRPO: Training Graph Flow Models with Reinforcement Learning
CELL: A Causal Perspective for Fairness-aware Graph Adaptation
Data Reconstruction: Identifiability and Optimization with Sample Splitting
Improving Classifier-Free Guidance of Flow Matching via Manifold Projection
Beyond Gemini-3-Pro: Revisiting LLM Routing and Aggregation at Scale
Bridging Structure and Semantics: Uncertainty-Modulated Dual-Path Diffusion for Robust Text-Attributed Graph Learning
When Do Graph Foundation Models Transfer? A Data-Centric Theory
Can VLMs Diagnose and Recover from VLA Manipulation Faults?
Message Passing on the Edge: Towards Scalable and Expressive GNNs
A Stronger Benchmark for Online Bilateral Trade: From Fixed Prices to Distributions
Regret Minimization With a Crowd of Awakening Experts
Vision-DeepResearch: Incentivizing DeepResearch Capability in Multimodal Large Language Models
Obliviate: Efficient Unlearning in Recommender Systems
GFMate: Empowering Graph Foundation Models with Pre-training-agnostic Test-time Prompt Tuning
Beyond Soft Labels: Unifying Dataset Pruning and Distillation for Efficient Large-scale Compression
Bridging the Knowledge-Prediction Gap in LLMs on Multiple-Choice Questions
Generalist Graph Anomaly Detection via Prototype-Based Distillation
Sheaf Neural Networks on SPD Manifolds: Second-Order Geometric Representation Learning
Revisiting Positive Samples in Graph Contrastive Learning: From the Perspective of Message Passing
Critique-Guided Distillation for Robust Reasoning via Refinement
Spurious Correlation Learning in Preference Optimization: Mechanisms, Consequences, and Mitigation via Tie Training
Coordinated Disentanglement with Iterative Mode Discovery Under Hidden Correlations
See What Matters: Differentiable Grid Sample Pruning for Generalizable Vision-Language-Action Model
GSRQ: Gain-Shape Residual Quantization for Sub-1-bit KV Cache
BIT-LLM: Brain Instruction Tuned LLM with persistent Cross-Attention for fMRI-to-Text Decoding
Generative Representation Learning on Hyper-relational Knowledge Graphs via Masked Discrete Diffusion
Modeling Spectral Energy Shifts in Spatio-Temporal Graph Anomaly Detection
Near-Optimal Dynamic Matching via Coarsening with Application to Heart Transplantation
On Computation and Reinforcement Learning
Towards Generative Graph Matching for Graph Edit Distance Computation
AsyncSpade: Efficient Test-Time Scaling with Asynchronous Sparse Decoding
Zero-Shot Off-Policy Learning
Learning Permutation from Structure Without Supervision
What Information Matters? Graph Out-of-Distribution Detection via Tri-Component Information Decomposition
Moving Beyond Sparse Grounding with Complete Screen Parsing Supervision
RLIE: Rule Generation with Logistic Regression, Iterative Refinement, and Evaluation for Large Language Models
Large Vision–Language Models Get Lost in Attention
Real-World Unsupervised Models Generalize to Predict Brain Responses to Out-of-Distribution Stimuli
From Reward-Free Representations to Preferences: Rethinking Offline Preference-Based Reinforcement Learning
TriForces: Augmenting Atomistic GNNs for Transferable Representations
ArenaRL: Scaling RL for Open-Ended Agents via Tournament-based Relative Ranking
Draft-and-Audit Reinforcement Learning for Optimization Modeling
Beyond Description: Federated Adaptation via Semantic-Visual Prototype Alignment
When Attributes Disagree: Gradient Conflict in Image Aesthetic Assessment
ComplexMCP: Evaluation of LLM Agents in Dynamic, Interdependent, and Large-Scale Tool Sandbox
Two Calm Ends and the Wild Middle: A Geometric Picture of Memorization in Diffusion Models
Anomaly-Preference Image Generation
REAR: Test-time Preference Realignment through Reward Decomposition
Aitchison Embeddings for Learning Compositional Graph Representations
FLARE-AI: Flaw Reporting for AI
Less is Enough: Synthesizing Diverse Data in Feature Space of LLMs
Desirable Effort Fairness and Optimality Trade-offs in Strategic Learning
Efficient Skill Grounding via Code Refactoring with Small Language Models
Federated Distillation for Whole Slide Image via Gaussian-Mixture Feature Alignment and Curriculum Integration
The Geometric Origin of Grokking: Accelerating Generalization via Active Structural Reorganization
The Shadow Price of Reasoning: Economic Perspective on Optimal Budget Allocation for LLMs
Are Tools Always Beneficial? Learning to Invoke Tools Adaptively for Dual-Mode Multimodal LLM Reasoning
Model-Free Robust Average-Reward Reinforcement Learning with Sample Complexity Analysis
PADA-Coder: Improving Plan-Following Code Generation via Perturbation-Verified Attention Distillation and Dynamic Alignment
Rank-guided Diffusion for Noise Few-Shot Learning
TimeSeed: Effective Time Series Forecasting with Sparse Endogenous Variables
Persistent Backdoor Attacks in Class-Incremental Learning via Structural Invariant Anchoring
Multicalibration Yields Better Matchings
Executable Agentic Memory for GUI Agent
CHB: A Diagnostic Toolkit for Hardness-Aware Clustering Evaluation
Predictable Compression Failures: Order Sensitivity and Information Budgeting for Evidence-Grounded Binary Adjudication
EvoCF: Multi-Agent Collaboration via Agentic Memory-Driven Evolutionary Counterfactual Planning
SpatialJB: How Text Distribution Art Becomes The "Jailbreak Key" for LLM Guardrails
Dropout Universality: Scaling Laws and Optimal Scheduling at the Edge-of-Chaos
Maximizing the Spectral Energy Gain in Sub-1-Bit LLMs via Latent Geometry Alignment
PaperBanana: Automating Academic Illustration for AI Scientists
Enhancing Neural Theorem Proving via High-Quality Proof Selection and Verifier Feedback
Optimal Design for Multinomial Logit Model with Applications to Best Assortment Identification
EXVERUS: Verus Proof Repair via Counterexample Reasoning
Predicting Future KV Utility: Global Combinatorial Optimization for Task-Agnostic KV Cache Eviction
OC-space: a Unifying Perspective on Verification of Tree Ensembles
Which LLM Multi-Agent Protocol to Choose?
RADAR: Redundancy-Aware Diffusion for Multi-Agent Communication Structure Generation
FRISM: Fine-Grained Reasoning Injection via Subspace-Level Model Merging for Vision–Language Models
Tucker Attention: A generalization of approximate attention mechanisms
Geometry-Aware Decoding with Wasserstein-Regularized Truncation and Mass Penalties for Large Language Models
Position: The Age of AI Agents Demands A New Scientific Paradigm To Sustain Trustworthy Science
Data Difficulty and the Generalization–Extrapolation Tradeoff in LLM Fine-Tuning
SPLIT-VLM: Salience-Guided Partitioning towards Local Coverage for Importance-Aware Token Dropping in Vision-Language Models
Random Scaling of Emergence Capabilities
Agent Learning via Early Experience
SafeSearch: Automated Red-Teaming of LLM-Based Search Agents
Clustered Influence Functions
Evaluating Sample Utility for Efficient Data Selection by Mimicking Model Weights
HyPOLE: Hyperproperty-Guided Multi-Agent Reinforcement Learning under Partial Observation
Root Cause Analysis of Failures in Microservices via Bayesian Root Cause Discovery
Singular Vectors of Attention Heads Align with Features
SliceFine: The Universal Winning-Slice Hypothesis for Pretrained Networks
Low-Rank and Sparsity Are All You Need: Exploring Robust Hierarchical Latent Subspaces for Transferable Adversarial Attack
Synergistic Intra- and Cross-Layer Regularization Losses for MoE Expert Specialization
Spectral Reach: Understanding Neural Scaling through Kernel Alignment Dynamics
Flow for Future: Geometric SE(3)-Equivariant Flow Matching for 3D Trajectory Prediction
Self-Captioning Multimodal Interaction Tuning: Amplifying Exploitable Redundancies for Robust Vision Language Models
On the Theoretical Limitations of Embedding-based Link Prediction
Learning Hamiltonian Flow Maps: Mean Flow Consistency for Large-Timestep Molecular Dynamics
CorrSteer: Generation-Time LLM Steering via Correlated Sparse Autoencoder Features
MultiPriv: Benchmarking Individual-Level Privacy Reasoning in Vision-Language Models
Power-Calibrated LLM Watermarking: A Statistical Framework
Low Kruskal-Rank Adaptation
Large Language Models as Topological Thinkers: A Benchmark on Graph Persistent Homology
You Don’t Need All That Attention: Surgical Memorization Mitigation in Text-to-Image Diffusion Models
Optimizing Rank for High-Fidelity Implicit Neural Representations
Probing How Scalable Table Data Enhances General Long-Context Reasoning
Linear Regression with Unknown Truncation Beyond Gaussian Features
Variational Entropic Optimal Transport
Hierarchical Representations for Cross-task Automated Heuristic Design using LLMs
Generalized Linear Bandits with Memory
Multi-Agent Teams Hold Experts Back
MePo: Meta Post-Refinement for Rehearsal-Free General Continual Learning
Partial Ring Scan: Revisiting Scan Order in Vision State Space Models
Universality, Function Composition, and Algorithm Emulation All In-Context
Plan for Speed: Dilated Scheduling for Masked Diffusion Language Models
Fixed Budget is No Harder Than Fixed Confidence in Best-Arm Identification up to Logarithmic Factors
Trajectory Seriation via Spectral Tangent Alignment and Global Embedding
Multi-task Linear Regression without Eigenvalue Lower Bounds: Adaptivity, Robustness and Safety
Negatives-Dominant Contrastive Learning for Generalization in Imbalanced Domains
MacroGuide: Topological Guidance for Macrocycle Generation
Gradient Descent with Large Step Size Restores Symmetry in Deep Linear Networks with Multi-Pathway
From Bits to Rounds: Parallel Decoding with Exploration for Diffusion Language Models
Position: Natural Language Should Not Fully Replace Formal Languages
Sampling from Your Language Model One Byte at a Time
Learning Sparse Visual Representations via Spatial-Semantic Factorization
MAD: Manifold Attracted Diffusion
Position: Express Your Doubts — Probabilistic World Modeling Should not be Based on Token *logprobs*
MVISTA-4D: View-Consistent 4D World Model with Test-Time Action Inference for Robotic Manipulation
KernelCraft: Benchmarking for Agentic Close-to-Metal Kernel Generation on Emerging Hardware
Differential Smoothing Mitigates Sharpening and Improves LLM Reasoning
Enhancing Conformal Prediction via Class Similarity
Where Concept Erasure Should Occur: Concept–Layer Alignment in Text-to-Video Diffusion Models
Mechanisms of Introspective Awareness
Generalized Correctness Models: Learning Calibrated and Cross-Model Correctness Predictors from Historical Patterns
Revisiting Efficiency–Accuracy Scaling in Mixture-of-Experts Architectures
A World in Pieces: Structural Certification of General Agents
ScalingAR: Scaling Confidence for Autoregressive Image Generation
ITSPACE: Monotone Gaussian Optimal Transport Updates
The Value of Variance: Mitigating Debate Collapse in Multi-Agent Systems via Uncertainty-Driven Policy Optimization
Evolutionary Generation of Multi-Agent Systems
Local Minima in Quadratic-Penalty Relaxations of Binary Linear Programs
Show, Don't Tell: Morphing Latent Reasoning into Image Generation
TextAtlas5M: A Large-Scale Dataset for Long Text Image Generation
Cooperative variance estimation and Bayesian neural networks disentangle aleatoric and epistemic uncertainties
Stable Asynchrony: Variance-Controlled Off-Policy RL for LLMs
Profiling the Irrational Agent: Cognitive Modeling of LLM Behaviors in Sequential Jailbreaks
Learning-Augmented Scalable Linear Assignment Problem Optimization via Neural Dual Warm-Starts
GPan-LoRA: Gaussian Process Amortized Networks for Bayesian Low-Rank Adaptation in Large Language Models
See the Emotion: A Facial Emoji Proxy Modeling for EEG Emotion Recognition
Is Code Better Than Language for Algorithmic Reasoning?
OPIC: Enhancing Language Model Merging via Optimizing In-Context Capability
Delayed Momentum Aggregation: Communication-efficient Byzantine-robust Federated Learning with Partial Participation
CHESS: Chebyshev Spectral Synthesis for Trajectory Condensation
Dive into the Scene: Breaking the Perceptual Bottleneck in Vision-Language Decision Making via Focus Plan Generation
Demystifying Entropy Control in LLM RL Training: Theoretical Analysis and Dynamic Scheduling
Dispersion Loss Counteracts Embedding Condensation and Improves Generalization in Small Language Models
Federated Sketching LoRA: A Flexible Framework for Heterogeneous Collaborative Fine-Tuning of LLMs
Deep Learning for Bioimaging: What are we actually learning?
SE3Set: Harnessing Equivariant Hypergraph Neural Networks for Molecular Representation Learning
VGGT-Motion: Motion-Aware Calibration-Free Monocular SLAM for Long-Range Consistency
Formal Concept Lattices are Good Semantic Scaffolds for Concept-Based Learning
XRPO: Pushing the Limits of GRPO with Targeted Exploration and Exploitation
From Text to Forecasts: Bridging Modality Gap with Temporal Evolution Semantic Space
When Single Answer Is Not Enough: Rethinking Single-Step Retrosynthesis Benchmarks for LLMs
TextResNet: Decoupling and Routing Optimization Signals in Compound AI Systems via Deep Residual Tuning
How do LLMs Compute Verbal Confidence?
Batched First-Order Methods for Parallel LP Solving in MIP
AgentExpt: Automating AI Experiment Design with LLM-based Resource Retrieval Agent
FlowState: Sampling-Rate‑Equivariant Time‑Series Forecasting
Local Covariate Selection for Average Causal Effect Estimation without Pretreatment and Causal Sufficiency Assumptions
Reinforcement Learning with Verifiable Rewards: GRPO's Loss, Dynamics, and Success Amplification
Random Selection Reveals Implicit Knowledge Consensus in Code Generation
TIC-VLA: A Think-in-Control Vision-Language-Action Model for Robot Navigation in Dynamic Environments
Training-Free Guided Diffusion for Planning: A Unified Framework via Doob’s h-Transform with Safety Guarantees
Towards Pareto-Optimal Tool-Integrated Agents with Pareto Ranking Policy Optimization
Memora: A Harmonic Memory Representation Balancing Abstraction and Specificity
View Space: Learning Representation across Arbitrary Graphs
Dual Optimal Transport for Multi-Concept Composition: Structural Alignment and Texture Injection in Diffusion Models
Reinforcing Real-world Service Agents: Balancing Utility and Cost in Task-oriented Dialogue
SpanNorm: Reconciling Training Stability and Performance in Deep Transformers
PHALAR: Phasors for Learned Musical Audio Representations
Efficient Mismatch-Tolerant Coding for Model-Driven Compression
Advancing Analytic Class-Incremental Learning through Vision-Language Calibration
PACE: Parameter Change for Unsupervised Environment Design
Efficient Code Analysis via Graph-Guided Large Language Models
From Memorization to Parameter Interference: How Overtraining Experts Harms Model Merging
Demystifying When Pruning Works via Representation Hierarchies
Mitigating Mask Prior Drift and Positional Attention Collapse in Large Diffusion Vision-Language Models
PhenoBrain: Phenotype-Conditioned Long-Range Communication for Multi-Modal Brain Network Analysis
Adversarial Attacks and Robust Training for Hypergraph Neural Networks
Sparse Autoencoders for Interpretable Emotion Control in Text-to-Speech
Prompt Injection as Role Confusion
EduMirror: Modeling Educational Social Dynamics with Value-driven Multi-agent Simulation
Unlearning in Diffusion Models: A Unified Framework with KL Divergence and Likelihood Constraints
Reinforcement Learning with Evolving Rubrics for Deep Research
Efficient Continuous-Depth Modeling with GRU Equivalents
Variational Inference for Uncertain Optimal Transport via Sinkhorn Parametrization
EnerGS: Energy-Based Gaussian Splatting under Partial Geometric Observability
Scaling Real-World Robot Policy Evaluation via Discrete Diffusion World Model
Causal Attention with Lookahead Keys
CiteGuard: Conformal False-Discovery Control for Faithful Retrieval-Augmented Generation
Information-Theoretic Generalization Bounds for VAEs: A Role of Encoder and Latent Variable
The Geometry of Updates: Fisher Alignment at Vocabulary Scale
RoboMME: Benchmarking and Understanding Memory for Robotic Generalist Policies
MapDream: Task-Driven Map Learning for Vision-Language Navigation
TrustworthyQENN: A Quantum Evidential Neural Network Based on Complex-Valued Contrastive Learning for Uncertainty Pattern Classification
A Strictly Proper Scoring Rule and a Calibration Metric for Interval-Censored Data Analysis
Retrieval-Aware Distillation for Transformer-SSM Hybrids
Directly Optimizing Natural Language Explanations for Behavioral Faithfulness: Simulatability and Recoverability
LassoFlexNet: a Flexible Neural Architecture for Tabular Data
Fine-to-Coarse Fairness-Informed Multi-View Clustering
Judgment Operators: A Composition-Invariant Substrate for Multi-Agent Action Spaces
Multimodal Nested Learning for Decoupled and Coordinated Optimization
Scalable RF Simulation in Generative 4D Worlds
Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective
SEPS: Semantic-Enhanced Patch Slimming Framework for Fine-Grained Cross-Modal Alignment
Distributionally Robust Set Representation Learning Under Inference-Time Element Corruption
Re-FORC: Adaptive Reward Prediction for Efficient Chain-of-Thought Reasoning
Delving into Non-Exchangeability for Conformal Prediction in Graph-Structured Multivariate Time Series
Training-Free Coverless Multi-Image Steganography with Access Control
One Step Forward and K Steps Back: Better Reasoning with Denoising Recursion Models
WaveSSM: Multiscale State-Space Models for Non-stationary Signal Attention
Optimizing Language Models for Crosslingual Knowledge Consistency
Federated Multi-view Clustering for Remote Sensing Data
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
Coevolutionary Continuous Discrete Diffusion: Make Your Diffusion Language Model a Latent Reasoner
Time-series forecasting through the lens of dynamics
SIMoE: A Probabilistic Framework for Cardinality-Constrained Routing in Mixture-of-Experts
Shuffle the Context: RoPE-Perturbed Self-Distillation for Long-Context Adaptation
AdaSplash-2: Faster Differentiable Sparse Attention
SynGR: Unleashing the Potential of Cross-Modal Synergy for Generative Recommendation
Efficient Neural Controlled Differential Equations via Attentive Kernel Smoothing
Evolution of Benchmark: Black-Box Optimization Benchmark Design through Large Language Model
On the Sample Efficiency of Inverse Dynamics Models for Semi-Supervised Imitation Learning
Fully Dynamic Coreset Spectral Clustering
A Queueing-Theoretic Framework for Stability Analysis of LLM Inference with KV Cache Memory Constraints
$\alpha$-PFN: Fast Entropy Search via In-Context Learning
Temper-Then-Tilt: Principled Unlearning for Generative Models through Tempering and Classifier Guidance
Gradient Flow Dynamics and Implicit Bias of Diagonal Linear Networks under Infinitesimal Initialization
Dynamics Reveals Structure: Challenging the Linear Propagation Assumption
Partitioning for Intrinsic Model Inversion Resistance in Collaborative Inference
Agent JIT Compilation for Latency-Optimizing Computer-Use Agent Planning and Scheduling
iLoRA: Bayesian Low-Rank Adaptation with Latent Interaction Graphs for Microbiome Diagnosis
A Diagnostic Study of Multi-Agent LLMs for Real-World Debates
Adaptive Preconditioners Trigger Loss Spikes in Adam
Inference-Time Conformal Reasoning with Valid Factuality Control for Large Language Models
VALUEFLOW: Toward Pluralistic and Steerable Value-based Alignment in Large Language Models
Size Transferability of Graph Convolutional Networks across Sparsity: A Generalized Graphon Perspective
Rethinking Convergence in MoE Training: The Role of Routing Sparsity
Ubiquity of Homeostatic Hebbian Dynamics in Regularized Learning
Diagnosing the Reliability of LLM-as-a-Judge via Item Response Theory
Identifiable Token Correspondence for World Models
AudioMosaic: Contrastive Masked Audio Representation Learning
Narrowing the ANN–SNN Gap for 1D Signal Classification with Multi-Scale Temporal Encoding and Sparsity-Regularized Transform Encoding
Query Lens: Interpreting Sparse Key-Value Features with Indirect Effects
Branch Scaling Manifests as Implicit Architectural Regularization for Improving Generalization in Overparameterized ResNets
Quantum Robust Inner Minimization for Reinforcement Learning with Quadratic Speed-Up in Query Complexity
Decomposing Out-of-Distribution Error in Conditional Flow Matching via Wasserstein Geometry
Who Said Neural Networks Aren't Linear?
Physics-informed coarsening for multigrid graph neural networks surrogates
Fix the Mind, Not the Move: Interpretable AI Assistance via Knowledge-Gap Localization
INDEXGUARD: Index-only Backdoor Vetting for Secure Federated PEFT of Large Language Models
Prototype-Based Test-Time Adaptation of Vision-Language Models
The ACE Protocol: Operationalizing Language Model Activations for Better Calibration and Utility
Divide and Contrast: Learning Robust Temporal Features without Augmentation
Predictive Prefetching for Retrieval-Augmented Generation
Preserving Plasticity in Continual Learning via Dynamical Isometry
WF-Bench: A Benchmark for Neural-Network WaveFunction Expressivity and Scaling Laws
PAC-Bayesian Reinforcement Learning Trains Generalizable Policies
Target-Aware Bandit Allocation for Scalable Surrogate Optimization in Chemical Space
GraphPFN: A Prior-Data Fitted Network for Graph Node-Level Tasks
A Geometric Analysis of Small-sized Language Model Hallucinations
PFT: Phonon Fine-tuning for Machine Learned Interatomic Potentials
Deliberate Evolution for Sample-Efficient Symbolic Regression with LLM
ACON: Optimizing Context Compression for Long-horizon LLM Agents
Contrastive Reasoning Alignment: Reinforcement Learning from Hidden Representations
FedPDG: Prediction Discrepancy–Guided Data Generation for Heterogeneous Federated Learning
Resting Neurons, Active Insights: Robustify Activation Sparsity for Large Language Models
RSA-CP: Efficient Conformal Prediction in Small-Sample Regimes via Random Score Alignment
JanusPipe: Efficient Pipeline Parallel Training for Machine Learning Interatomic Potentials
URS: A Unified Neural Routing Solver for Cross-Problem Zero-Shot Generalization
Efficient Prediction of SO(3)-Equivariant Hamiltonian Matrices via SO(2) Local Frames
RiskZero: Plan More to Risk Less with a Learned Model
ReCoG: Relational and Compact Context Graph Learning for Few-shot Molecular Property Prediction
SpecPL: Disentangling Spectral Granularity for Prompt Learning
VT-Bench: A Unified Benchmark for Visual-Tabular Multi-Modal Learning
SCalDA: Semantics-Calibrated and Diffusion-Enhanced Data Augmentation
Resolution as a Direction: Vector-Panning Feature Alignment for Cross-Resolution Re-Identification
Exploring Relational Reasoning Capabilities in LLMs with REL
SpaceVista: All-Scale Visual Spatial Reasoning from mm to km
Tiny Brains, Giant Impact: Uncovering the Keystone Neurons of LLM with Just a Few Prompts
MoSA: Motion-constrained Stress Adaptation for Mitigating Real-to-Sim Gap in Continuum Dynamics via Learning Residual Anisotropy
A$^2$SG: Adaptive and Asymmetric Surrogate Gradients for Training Deep Spiking Neural Network
Coloring the Noise: Adversarial Sobolev Alignment for Faithful Image Super Resolution
Video-in-the-Loop: Span-Grounded Long Video QA with Interleaved Reasoning
Adaptive Multiscale Binary Expansion Tests for Independence
Value Aggregation with Uncertainty in Online Decentralized MARL
FAIL: Flow Matching Adversarial Imitation Learning for Image Generation
Unified Multimodal Visual Tracking with Dual Mixture-of-Experts
Differentially Private Continual Release with Relative Error
Foresee-to-Ground: From Predictive Temporal Perception to Evidence-Driven Reasoning for Video Temporal Grounding
SCoA: Revisiting Domain Generalized Object Detection with Style-Conditioned Adaptation
Constrained Meta Reinforcement Learning with Provable Test-Time Safety
Unified Safe In-context Image Generation in Multimodal Diffusion Transformers
Bridging Local–Global Dissonance: Learning from Compressive Measurements for Hyperspectral Reconstruction
SLIP-RS: Structured-Attribute Language-Image Pre-Training for Remote Sensing Object Detection
Towards a Science of AI Agent Reliability
From Perception to Planning: Evolving Ego-Centric Task-Oriented Spatiotemporal Reasoning via Curriculum Learning
NoiseSDF2NoiseSDF: Learning Clean Neural Fields from Noisy Supervision
ERGeoBench: A Comprehensive Benchmark for Embodied Reasoning and Geo-localization in Multimodal Large Language Models
Discovering Symmetry Groups with Flow Matching
TVDRNet: Text-driven Viewpoint Optimization via Differentiable Rendering for 3D Reasoning Segmentation
COGNOS: Universal Enhancement for Time Series Anomaly Detection via Constrained Gaussian-Noise Optimization and Smoothing
Cerebellar-Inspired Residual Control for Fault Recovery: From Inference-Time Adaptation to Structural Consolidation
Remove the Ambiguity: Few-shot Multimodal Anomaly Detection Using Crossmodal Feature Replacers
Linear Causal Representation Learning by Topological Ordering, Pruning, and Disentanglement
Computing Provable Bounds for Exact Shapley Values of Neural Networks
SAGE-NAS: Synergizing LLM-Based Semantic Agent with Graph-Based Evaluator for Neural Architecture Search
Constrained Bayesian Experimental Design via Online Planning
Conformal Reliability: A New Evaluation Metric for Conditional Generation
RSAgent: Learning to Reason and Act via Multi-Turn Tool Invocations for Text-Guided Segmentation
The data manifold under the microscope
Breaking the Synthetic-Real Domain Shortcut for Training-Free Generative Replay-based Class Incremental Learning
On Effectiveness and Efficiency of Agentic Tool-calling and RL Training
Benchmarking and Enhancing VLM for Compressed Image Understanding
LayerT2V: A Unified Multi-Layer Video Generation Framework
Bias-Spectrum Neural Processes for Parametric PDEs: Architecture Priors Meet PDE Constraints
CARE: Confounder-Aware Aggregation for Reliable LLM Evaluation
Temporal-aware Flow Matching for Video Generation with Temporally Coherent Motion
Sem-Detect: Semantic Level Detection of AI Generated Peer-Reviews
SVRG and Beyond via Posterior Correction
DiffThinker: Towards Generative Multimodal Reasoning with Diffusion Models
VideoVeritas: AI-Generated Video Detection via Perception Pretext Reinforcement Learning
CalPro: Prior-Aware Evidential Conformal Prediction with Structure-Aware Sensitivity Bounds for Protein Structures
Context Forcing: Consistent Autoregressive Video Generation with Long Context
Multi-Integration of Labels across Categories for Component Identification (MILCCI)
TFRBench: A Reasoning Benchmark for Evaluating Forecasting Systems
Split Group Knockoffs: Controlling False Discovery Rate in Transformational Group Sparsity
PPDL: LLM-Based Flows as Probabilistic Programs
STORM: Segment, Track, and Object Re-Localization from a Single Image
REG: In-Sample RL via Regularizing the Evaluation Gap
GP2F: Cross-Domain Graph Prompting with Adaptive Fusion of Pre-trained Graph Neural Networks
Joint Geometric and Trajectory Consistency Learning for One-Step Real-World Super-Resolution
InfoGeo: Information-Theoretic Object-Centric Learning for Cross-View Generalizable UAV Geo-Localization
Unleashing Implicit Rewards: Prefix-Value Learning for Distribution-Level Optimization
From Correspondence to Actions: Human-Like Multi-Image Spatial Reasoning in Multi-modal Large Language Models
CoopEval: Benchmarking Cooperation-Sustaining Mechanisms and LLM Agents in Social Dilemmas
AURA: Visually Interpretable Affective Understanding via Robust Archetypes
Variance Driven Exploration: A Provable and Efficient Methodology for Pure Exploration in Highly Stochastic Environments
Semantic Editing with Coupled Stochastic Differential Equations
DLLMQuant: A Post-Training Quantization Framework Tailored for Diffusion-Based Large Language Models
Escaping the Diversity Trap in Robotic Manipulation via Anchor-Centric Adaptation
Select to Think: Unlocking SLM Potential with Local Sufficiency
DAISI: Data Assimilation with Inverse Sampling using Stochastic Interpolants
Process Reward Agents for Steering Knowledge-Intensive Reasoning
Regulating Anatomy-Aware Rewards via Trajectory-Integral Feedback for Volumetric Computed Tomography Analysis
Hierarchical Causal Abduction: A Foundation Framework for Explainable Model Predictive Control
Efficient Preference Poisoning Attack on Offline RLHF
Mitigating Staleness in Asynchronous Pipeline Parallelism via Basis Rotation
Why Deep Jacobian Spectra Separate: Depth-Induced Scaling and Singular-Vector Alignment
Benchmarking the Scientific Mind: Toward Evaluation of Complex-Reasoning Biomedical VQA
Beyond Log Likelihood: Probability-Based Objectives for Supervised Fine-Tuning across the Model Capability Continuum
CREDIT: Certified Ownership Verification of Deep Neural Networks Against Model Extraction Attacks
Differential syntactic and semantic encoding in LLMs
LEAP: Zone-Aware MCTS for LLM Self-Speculative Decoding
The Double Dilemma in Multi-Task Radiology Report Generation: A Gradient Dynamics Analysis and Solution
LALM-as-a-Judge: Benchmarking Large Audio-Language Models for Safety Evaluation in Multi-Turn Spoken Dialogues
Hybrid-Gym: Training Coding Agents to Generalize Across Tasks
Dynamic Decision Learning: Test-Time Evolution for Abnormality Grounding in Rare Diseases
Structured Multi-modal Graph Disentanglement for Psychiatric Diagnosis
BRIDGE: Predicting Human Task Completion Time From Model Performance
Rare Event Analysis of Large Language Models
DSENet: A Novel Dual-Stream Enhancement Network for Multi-Scale Non-Stationary Time Series Forecasting
TwinWeaver: An LLM-Based Foundation Model Framework for Pan-Cancer Digital Twins
DiscoForcing: A Unified Framework for Real-Time Audio-Driven Character Control with Diffusion Forcing
ORBIT: A Prognostic World Model for Ocular Reasoning Based on Imagined Trajectories
Maximum-Likelihood Learning of Latent Dynamics Without Reconstruction
Correctness-Optimized Residual Activation Lens (CORAL): Transferrable and Calibration-Aware Inference-Time Steering
Reason with Thumbnails, Answer with Focus: An Efficient and Effective Paradigm for Multimodal Grounded Visual Reasoning
Agentic Framework for Epidemiological Modeling
MUSA-PINN: Multi-scale Weak-form Physics-Informed Neural Networks for Fluid Flow in Complex Geometries
Heavy-tailed Physics-Informed Neural Networks
Fox in the Henhouse: Supply-Chain Backdoor Attacks Against Reinforcement Learning
One-shot Conditional Sampling: MMD meets Nearest Neighbors
Position: Assistive Agents Need Accessibility Alignment
Beyond Text-to-SQL: Can LLMs Really Debug Enterprise ETL SQL?
Randomized Feasibility Methods for Constrained Optimization with Adaptive Step Sizes
EGG: An Expert-Guided Agent Framework for Kernel Generation
Deep Neural Network Regression with Functional Covariates
Black-Box Detection of LLM-Generated Text Using Generalized Jensen Shannon Divergence
LipoPU: Pocket-level Prediction of Lipid-Protein Interactions via Positive-Unlabeled Learning
Convex Low-resource Accent-Robust Language Detection in Speech Recognition
Spectral-Progressive Thought Flow for Lightweight Multimodal Reasoning
Unsupervised Partner Design Enables Robust Ad-hoc Teamwork
Chain-of-Goals Hierarchical Policy for Long-Horizon Offline Goal-Conditioned RL
IntentRL: Training Proactive User-intent Agents for Open-ended Deep Research via Reinforcement Learning
Scaling Laws in Model Fine-tuning for Audio DeepFake Detection
Fast Estimation for Forest Matrix of Signed Graphs
SWE-fficiency: Can Language Models Optimize Real-World Repositories on Real Workloads?
Efficiently Training Time-to-First-Spike Spiking Neural Networks from Scratch
Efficiently Solving Discounted MDPs via Predictions with Unknown Prediction Errors
FOCA: Future-Oriented Conditioning for Data-Efficient Vision-Language-Action Adaptation
ViEEG: Hierarchical Visual Neural Representation for EEG Brain Decoding
Supervised Graph Contrastive Learning for Gene Regulatory Networks
AudioChat: Unified Audio Storytelling, Editing, and Understanding with Transfusion Forcing
CLoVE: Personalized Federated Learning through Clustering of Loss Vector Embeddings
Procedural Generation Of Algorithm Discovery Tasks in Machine Learning
Unlearning with Asymmetric Sources: Improved Unlearning-Utility Trade-off with Public Data
AgentHijack: Benchmarking Computer Use Agent Robustness to Common Environment Corruptions
SpikingLM: Towards Fully Spiking Language Model
Resolving the Timestep Scaling Paradox in Spiking Neural Networks with a Timestep-Scalable Neuron Model
SmoothSpike: Spiking Transformer with Learnable Hadamard Transformation
Reward Shaping for Inference-Time Alignment: A Stackelberg Game Perspective
The Consistency Trap in LLMs: Generator-Evaluator Agreement and Vulnerability to Mistakes
Tackling Length Inflation Without Trade-offs: Group Relative Reward Rescaling for Reinforcement Learning
HInT: Hypergraph Infusion at the Structural Layers Improves Table Understanding
Spik4lite: Refactoring Neuromorphic Sparsity for Efficient Spiking Neural Networks on Commodity Edge Devices
Position: Evidence and Implications of Texture Bias in Deep Neural Networks
Position: Uncertainty Quantification in LLMs is Just Unsupervised Clustering
AdaS: Adaptive Gradient Descent for Spiking Transformers
Temporal Weighted Encoding: Towards Maximal-Capacity Spike Coding for ANN–SNN Conversion
Position: Breaking the Dual Curse of Multilingual AI Requires Socio-Technical Guardrails, Not Post-Hoc Alignment
Position: Temporal Measurement Interval Determines Computational and Model Complexity in Single-Cell Perturbation Analysis
DriveWorld-VLA: Unified Latent-Space World Modeling with Vision–Language–Action for Autonomous Driving
Position: Why a Dynamical Systems Perspective is Needed to Advance Time Series Modeling
Position: Current Benchmarking Hinders Real Progress in Deep Learning for Time Series Forecasting
Position: Bridge Human Interpretation and Machine Representation With Explicit Specification For Qualitative Data Analysis In LLM Era
GLARE: Scalable Neuro-Symbolic Reward Shaping for LLM Agents via Group-Level Automata
KineFlow: Kinematic Second-Order Flow Matching for Time-Series Forecasting
DropoutTS: Sample-Adaptive Dropout for Robust Time Series Forecasting
Position: Current Model Cards Are Insufficient for Downstream Governance of Open-Weight Foundation Models
Position: We Need Practical AI Alignment Methods that Mirror Human Reasoning
Position: Video LLMs Must Not Ignore the Pixel Dynamics in Plain Sight
Time-Conditioned Foreseeing: An EHR-Specific Foundation Model for Irregular Dynamics and Calendrical Time
PATRA: Pattern-Aware Alignment and Balanced Reasoning for Time Series Question Answering
Position: Creating High-Fidelity Synthetic Training Data Should Employ Multi-level Optimization
Position: Agentic Systems Should be General
KITE: Knowledge-Guided Probabilistic Modeling for Time Series Forecasting with Exogenous Variables
Generative Modeling of Irregular Time Series via SDE-Induced Continuous-Discrete Variational Inference
Position: Time-Series Foundation Models Require Explicit Domain-Level Benchmarks
Position: Vision encoders should be image size agnostic and task driven
Position: Collusion Risks Among AI Reasoning Agents Justify Certification Requirements for Making Market Decisions
Position: We need to re-think the concept of “real” images.
Position: Trustworthy AI Suffers from Invariance Conflicts and Causality is The Solution
Position: Let's Develop Data Probes to Fundamentally Understand How Data Affects LLM Performance
ReAugment: Targeted Few-Shot Time Series Augmentation via Model Zoo-Guided Reinforcement Learning
Position: Evaluation of ECG Representations Must Be Fixed
Position: Embodied AI Requires a Privacy-Utility Tradeoff
TABX: A High-Throughput Sandbox Battle Simulator for Multi-Agent Reinforcement Learning
SpreadsheetArena: Decomposing Preference in LLM Generation of Spreadsheet Workbooks
Position: VLM Causal Reasoning Benchmarks Should Probe Temporal Understanding, Not Presume It
CORE: Conflict-Oriented Reasoning for General Multimodal Manipulation Detection
Leveraging Lineage Barcodes as Natural Augmentations for Contrastive Learning of Cell Fate in scRNA-seq Data
Position: Retire the "Positive Backdoor" Label—Secret Alignment Requires Strict and Systematic Evaluation
MALICE: Memory-aware Loop Invariants Generation on Symbolic Execution Traces
The Structural Origin of Attention Sink: Variance Discrepancy, Super Neurons, and Dimension Disparity
Harnessing Non-Adversarial Robustness in Large Language Models
Position: `AI Alignment' Encompasses Competing Technical Priorities
Position: Stop Reactively Patching Your Model Every Time and Start Proactive Test-Driven AI Development
Position: Safety Must Precede the Deployment of Open-Ended AI Agents
Position: Graph Condensation Needs a Reset—Move Beyond Full-dataset Training and Model-Dependence
Position: Early-Stage Quality Assurance in Annotation Pipelines Is More Cost-Effective Than Late-Stage Validation
Position: The Open Benchmark Paradox Must Be Resolved through Sovereign Medical Evaluation
Strat-Reasoner: Reinforcing Strategic Reasoning of LLMs in Multi-Agent Games
Towards Professional-Grade Financial Agents: Benchmarking, Tooling, and Structured Reasoning
Position: Predictive Uncertainty Is Not Enough -- Joint Distribution for Full Uncertainty Representation
QuArch: A Benchmark for Evaluating LLM Reasoning in Computer Architecture
NAACA: Training-Free NeuroAuditory Attentive Cognitive Architecture with Oscillatory Working Memory for Salience-Driven Attention Gating
Position: Deciphering the Functions of DNAs, RNAs, and Proteins Should Consider Multi-Modal Large Language Models
Convergence Rate of the Last Iterate of Stochastic Proximal Algorithms
Position: Universal Aesthetic Alignment Narrows Artistic Expression
DADP: Domain Adaptive Diffusion Policy
Position: Bridge the Gaps between AI Development and Regulation
On Group Relative Policy Optimization Collapse in Agent Search: The Lazy Likelihood-Displacement
Beyond Normalization: Rethinking the Partition Function as a Difficulty Scheduler for RLVR
Reparameterization Flow Policy Optimization
Informed Asymmetric Actor-Critic: Leveraging Privileged Signals Beyond Full-State Access
EVOLVING ROLLOUTS: Harnessing Historical Experience for Web Agent Evolution in Reinforcement Learning
Investigating Memory in RL with POPGym Arcade
Beyond Trajectory-Level Attribution: Graph-Based Credit Assignment for Agentic Reinforcement Learning
OmniAID: Decoupling Semantic and Artifacts for Universal AI-Generated Image Detection in the Wild
Bridging Tokens and Geometry: Token-wise 3D Supervision for CAD Generation
Agent Primitives: Reuseable Latent Building Blocks for Multi-Agent Systems
Non-Monotonic Autoregressive Sequence Model
TaskLoom: Weaving Knowledge Across Tasks in World Models
Advancing LLM Reasoning with Natural Language and Numerical Feedback
HiPER: Hierarchical Plan–Execute RL for Multi-Turn LLM Agents
UDM-GRPO: Stable and Efficient Group Relative Policy Optimization for Uniform Discrete Diffusion Models
In-Context Generation with Regional Constraints for Instructional Video Editing
Diversity-aware Weight Perturbation Promotes Robust Adaptation
MultiLoReFT: Decoupling Shared and Modality-Specific Subspaces in Multimodal Learning via Low-Rank Representation Fine-Tuning
Optimizing Visual Generative Models via Distribution-wise Rewards
EntroKV: Entropy-Guided Dynamic Budget Allocation for KV-Cache Compression
SAMT: Generating Structured Avatar Meshes and Textures from a Single Image
Population-Free Pareto Tracking for Sample-Efficient Multi-Policy MORL
Tvcache: A Tool-Value Cache for Post-Training LLM Agents
Meta-Learning with Generalized Ridge Regression: High-dimensional Asymptotics, Optimality and Hyper-covariance Estimation
Single-Head Attention in High Dimensions: A Theory of Generalization, Weights Spectra, and Scaling Laws
Over-Alignment vs Over-Fitting: The Role of Feature Learning Strength in Generalization
A Solvable High-Dimensional Model Where Nonlinear Autoencoders Learn Structure Invisible to PCA While Test Loss Misaligns With Generalization
CCLRec: Consensus-driven Contrastive Learning for LLM-enhanced Graph Recommendation
Tracing the Emergence of Symbol Grounding in Multimodal Language Models
Global Directional Priors with Local Statistical Validation for Scalable Causal Discovery
SSA: Sparse Sparse Attention by Aligning Full and Sparse Attention Outputs in Feature Space
Lifting Traces to Logic: Programmatic Skill Induction with Neuro-Symbolic Learning for Long-Horizon Agentic Tasks
AMA-Bench: Evaluating Long-Horizon Memory for Agentic Applications
PRISM: Sequence Modeling as Parallel Residual Iteration
Reasoning-Driven Synthetic Data Generation and Evaluation
Learning with Admissibility: Robust Fuzzy Hashing for Cross-Modal Retrieval with Noisy Labels
Decoupling The "What" and "Where" With Polar Coordinate Positional Embedding
Correspondence Cognitive Learning for Multi-Modal Object Re-Identification
Position: In Defense of Information Leakage in Concept-based Models
Seeing is Solving: Unlocking Efficient Multimodal RL via View Alignment
Learning Task-Sufficient World Models by Synergizing Agentic Exploration and Structured Modeling
Pruning at Initialisation through the lens of Graphon Limit: Convergence, Expressivity, and Generalisation
Causal Direct Preference Optimization for Distributionally Robust Generative Recommendation
When Iteration Helps and Hurts in Self-Training: Denoising vs. Signal Forgetting
Lookahead Path Likelihood Optimization for Diffusion LLMs
LithoDreamer: A Physics-Informed World Model for Multi-Stage Computational Lithography
Sparser, Faster, Lighter Transformer Language Models
Random Erasing vs. Model Inversion: A Promising Defense or a False Hope?
MiniX: Mitigating Low-Rank Collapse and Attention Bottlenecks in Tabular Foundation Models
Unified Time Series Explanations via Semi-Amortized Optimization and Instance-level Multi-Expert Knowledge Distillation
What Makes a Strong Model? A Unified Spectral Analysis of Knowledge Transfer over High-dimensional Linear Regression
Functional Equivalence in Attention: A Comprehensive Study with Applications to Linear Mode Connectivity
MVR-cache: Optimizing Semantic Caching via Multi-Vector Retrieval and Learned Prompt Segmentation
Rethinking the Trust Region in LLM Reinforcement Learning
Neural Modular Physics for Elastic Simulation
LieWarper: Geometry-Aware Motion Transfer via Lie Algebra
Mode Seeking meets Mean Seeking for Long Video Generation
Restoring Initial Noise Sensitivity in Text-to-Image Distillation through Geometric Alignment
Absorbing Quantization Error by Deformable Noise Scheduler for Diffusion Models
ADEPT: RL-Aligned Agentic Decoding of Emotion via Evidence Probing Tools — From Consensus Learning to Ambiguity-Driven Emotion Reasoning
Breaking the Capacity Bottleneck in Model-Heterogeneous Federated Learning via Gradual Model Restoration
Efficient Learning of Compositional Targets with Hierarchical Spectral Methods
SwiftPFN: Revisiting Row-Wise Attention–Only Tabular Foundation Models with Adaptive Early Exit
FedLog: Personalized Federated Classification with Less Communication and More Flexibility
Energy-Structured Low-Rank Adaptation for Continual Learning
Causal Representation Learning with Optimal Compression and Complex Treatments
Seeing Symbols, Missing Structure: A Real-World Handwritten Mathematical Expression Recognition Benchmark for Large Models
PGS: Effective LLM Code Refinement via Property-Oriented and Structurally Minimal Feedback
MemOCR: Layout-Aware Visual Memory for Efficient Long-Horizon Reasoning
Trajectory-Stabilized Inference for Diffusion-Based Video Inpainting
Sparse Models, Sparse Safety: Unsafe Routes in Mixture-of-Experts LLMs
Towards Spectroscopy: Susceptibility Clusters in Language Models
How Can Mamba Learn In Context with Outliers and Generalize Provably?
ManifoldKV: Training-Free KV Cache Compression via Euclidean Outlier Detection
Which Heads Matter for Reasoning? RL-Guided KV Cache Compression
Forensic Prompting with Dual-Action Policy Optimization for Vision-Language Forgery Detection and Localization
Learning in Bayesian Stackelberg Games With Unknown Follower's Types
NeuroMamba: A Universal Spatiotemporal Module for Robust Perception in Degraded Sensory Streams
Envy-Free Allocation of Indivisible Goods via Noisy Queries
Proxy Compression for Language Modeling
Selling Data as a Digital Good with Scaling Valuations
Rationality Measurement and Theory for Reinforcement Learning Agents
Necessary Conditions for Compositional Generalization of Embedding Models
Logarithmic Switching Regret for Online Convex Optimization
WET: Mitigating World-Conditioned Knowledge Conflicts via World Entropy Tethering
Optimal Transport with Symmetry Groups
MedCoG: Maximizing LLM Inference Density in Medical Reasoning via Meta-Cognitive Regulation
Physics from Video: Identifiability of Time-Invariant Second-Order ODEs under Minimal Trajectory Conditions
Optimal Attention Temperature Improves the Robustness of In-Context Learning under Distribution Shift in High Dimensions
Robust Learning via Nested Distributionally Robust Optimization
Unlocking the Potential of Continual Model Merging: An ODE Perspective
Global Convergence of Adaptive Sensing for Principal Eigenvector Estimation
Asymptotically Optimal Sequential Testing with Markovian Data
Identifiable Smooth Conjugacy Learning via Adversarial Orthogonality
On the Computational Complexity of Performative Prediction
Adaptive Testing for LLM Evaluation: A Psychometric Alternative to Static Benchmarks
FIBER: A Differentially Private Optimizer with Filter-Aware Innovation Bias Correction
On the Power of (Approximate) Reward Models for Inference-Time Scaling
Prompt Optimization with Minimal Unlabeled Input via Meta-Reasoning
Reflect-then-Correct: Rebalancing Task Optimization for Generalizable Meta-Reinforcement Learning via Distributional Value Error Reduction
4DPC$^2$hat: Towards Dynamic Point Cloud Understanding with Failure-Aware Bootstrapping
Training Deep Spiking Neural Networks without Normalization
UniSparse: Combining Weight Pruning and Spike Sparsification in Spiking Neural Networks
MemoryBench: A Benchmark for Memory and Continual Learning in LLM Systems
Learning to Rank from Incomplete Rankings
One-Step Gradient Delay is Not a Barrier for Large-Scale Asynchronous Pipeline Parallel LLM Pretraining
ExCyTIn-Bench: Evaluating LLM agents on Cyber Threat Investigation
Dynamic Linear Attention
PDFBench: A Benchmark for De Novo Protein Design from Function
Automatic Pruning Discovery for Large Language Models
Ski Rental with Distributional Predictions of Unknown Quality
Content-Style Identification via Differential Independence
Thinking in Structures: Evaluating Spatial Intelligence through Reasoning on Constrained Manifolds
Position: Digital Agents Require Unified Agent-Native Environments
BAT: Better Audio Transformer Guided by Convex Gated Probing
An analytic theory of convolutional neural network inverse problems solvers
Prompt Tuning for CLIP on the Pretrained Manifold
Beyond Problem Solving: UOJ-Bench for Evaluating Code Generation, Hacking, and Repair in Competitive Programming
VIBE: Disentangling Social Dynamics via Kinematics-Informed Variational Inference for Behavioral Emotion
TritonGym: A Benchmark for Agentic LLM Workflows in Triton GPU Code Generation
SCOUT: Active Information Foraging for Long-Text Understanding with Decoupled Epistemic States
Dynamics Within Latent Chain-of-Thought: An Empirical Study of Causal Structure
UniCode: Augmenting Evaluation for Code Reasoning
How can embedding models bind concepts?
From Conflict to Consensus: Boosting Medical Reasoning via Multi-Round Agentic RAG
MECAT: A Multi-Experts Constructed Benchmark for Fine-Grained Audio Understanding Tasks
Benchmarking World-Model Learning with Environment-Level Queries
Scaling the Prior: Size-Consistent Geometric Diffusion for 3D Molecular Generation
DocHop: Benchmarking Out-of-domain Multi-hop Reasoning in Information-Dense Documents
AtelierEval: Agentic Evaluation of Humans & LLMs as Text-to-Image Prompters
L-CUBE: Isolating Long-Context Capacity from Knowledge with Controllable Mutual Information Scaling
CUARewardBench: Benchmark for Evaluating Reward Models on Computer-using Agent Trajectories
Convex Distance Operator Transport: Convex and Geometry-Preserving Information
Do LLMs Signal When They’re Right? Evidence from Neuron Agreement
GICDM: Mitigating Hubness for Reliable Distance-Based Generative Model Evaluation
CB-SLICE: Concept-Based Interpretable Error Slice Discovery
Position: We Need A Unified Definition of Hallucination (It’s The World Model, Stupid!)
VisionWebDev: A Hierarchical Benchmark for Visual Website Development with Agent Verification
From Associations to Activations: Comparing Behavioral and Hidden-State Semantic Geometry in LLMs
Conditional KRR: Injecting Unpenalized Features into Kernel Methods with Applications to Kernel Thresholding
Kernel-based Maximum-of-difference Test for Two-sample Comparison
Online Conformal Prediction via Universal Portfolio Algorithms
Probabilistic Bisection Algorithm Provably Achieves Exponential Convergence
Online Packet Scheduling with Deadlines and Learning
UniFast-HGR: Scalable and Efficient Maximal Correlation for Multimodal Models
Identifying dependent components from multi-domain linear mixtures
CAMP: Coherent Alignment of Multimodal Prototypes for Explainable Complementary Learning
A Mechanistic Understanding of Sim-and-Real Co-Training in Generative Policies
Neural Collapse by Design: Learning Class Prototypes on the Hypersphere
Reasoning as an Attack Surface: Adaptive Evolutionary CoT Jailbreaks for LLMs
Learning to Reconfigure: Co-designing Reconfigurable robots for Heterogeneous Locomotion
Mixing Configurations for Downstream Prediction
Expand Neurons, Not Parameters
Distributional Inverse Reinforcement Learning
A Unifying View of Variational Generative Wasserstein Flows
Are Object-Centric Representations Better At Compositional Generalization?
Contrastive Symbolic Regression: Aligned Representations, Adaptive Prediction, and Diverse Ensembles
Multi-label learning with contrastive cluster self-supervision for 3D hierarchical semantic segmentation
Generative Large Neighborhood Search: Scalable Set Cover Optimization via Discrete Diffusion
R2R2: Robust Representation for Intensive Experience Reuse via Redundancy Reduction in Self-Predictive Learning
Emergent Visual Representations through Unsupervised Spiking Networks with Synaptic Pruning
SceneSmith: Agentic Generation of Simulation-Ready Indoor Scenes
Dual Mechanisms of Value Expression: Intrinsic vs. Prompted Values in Large Language Models
Boosting World Models Learning via Latent-Space Value Alignment
Reinforced Sequential Monte Carlo for Amortised Sampling
Hardware-Aware Dynamic Sparse Training for Large Output Spaces
Different Usage of Shared Components Explains Behavioral Variance in LLMs
Discrete Diffusion Samplers and Bridges: Off-Policy Algorithms and Applications in Latent Spaces
Deep Discriminative Structure Proxy Hashing for Cross-modal Retrieval
V1: Unifying Generation and Self-Verification for Parallel Reasoners
Unifying Stacking and Cascading for Efficient Ensemble Inference
Minimizing Mismatch Risk: A Prototype-Based Routing Framework for Zero-shot LLM-generated Text Detection
Beyond Accuracy: Latent Perturbations for Cognitive-Aware Diagnosis
Position: Carbon Footprint Reporting Should Be Routine in Machine Learning Research
Prototype-guided Bilateral Alignment Multimodal Federated Learning
USE : A Unified Self-Ensembling Framework for Test-Time Prompt Tuning
Server-Proximal Aggregation for Federated Domain-Incremental Learning under Partial Participation: Task-Uniform Convergence and Backward Transfer
Plasticity Activation via Polar Operator: A Plug-in Method for Balancing Stability and Plasticity
MARS-SQL: A Multi-Agent Reinforcement Learning Framework For Text-To-SQL
Rethinking Gating Mechanism in Sparse MoE: Handling Arbitrary Modality Inputs with Confidence-Guided Gate
Structure Abstraction and Generalization in a Hippocampus-Entorhinal Inspired World Model
One-Shot Weighted Ensemble Estimation for Federated Quantile Regression: Optimal Statistical Guarantees under Heterogeneous Structured Data
EPiC: Efficient Video Camera Control Learning with Precise Anchor-Video Guidance
On the Convergence Rate of LoRA Gradient Descent
QHyer: Q-conditioned Hybrid Attention-mamba Transformer for Offline Goal-conditioned RL
Quantized Maximum Likelihood Estimation under Normal Mean-Variance Mixture Model
Convergence Analysis of the Lion Optimizer in Centralized and Distributed Settings
Taming Stochastic Gradient Descent: Almost Sure Convergence and Saddle-Point Avoidance under $(L_{0},L_{1})$-Smoothness
Support-Proximity Augmented Diffusion Estimation for Offline Black-Box Optimization
EEmo-Logic: A Unified Dataset and Multi-Stage Framework for Comprehensive Image-Evoked Emotion Assessment
S2GS: Streaming Semantic Gaussian Splatting for Online Scene Understanding and Reconstruction
Scalable Bayesian Semi-supervised Clustering with Feature Selection and Adaptive Constraint Weighting
SEDRAS: Symbolically Evaluated Deep Research And Science
DR-MMSearchAgent: Deepening Reasoning in Multimodal Search Agents
A Cartesian-3j and nj Framework for Machine Learning Interatomic Potentials
Automated Formal Proofs of Combinatorial Identities via Wilf–Zeilberger Guidance and LLMs
Position: The Time for Sampling Is Now! Charting a New Course for Bayesian Deep Learning
Conditional Coverage Diagnostics for Conformal Prediction
When More Experts Hurt: Underfitting in Multi-Expert Learning to Defer
Position: If open source is to win, it must go public
Disentangling a Large Language Model’s Computation from its Chain-of-Thought
ExPLAIND: Unifying Model, Data, and Training Attribution to Study Model Behavior
Awakening Visual Reasoning: Mitigating Post-Training Failure in Vision-Text Compression
CLARITree: Cholesky and Lookahead Accelerations for Regression with Interpretable Piecewise Linear Trees
Beyond Additive Decompositions: Interpretability Through Separability
Agentic Model Predictive Questioning Control in Visual Design
Reviving Error Correction in Modern Deep Time-Series Forecasting
Efficient Rashomon Set Approximation for Decision Trees
How Good is Post-Hoc Watermarking With Language Model Rephrasing?
Explainable Federated Learning via Global–Local Attribution Alignment
AliMark: Enhancing Robustness of Sentence-Level Watermarks Against Text Paraphrasing
Bayesian Gated Non-Negative Contrastive Learning
What is Missing? Explaining Neurons Activated by Absent Concepts
Learning Treatment Allocations with Risk Control Under Partial Identifiability
Asymptotic Universal Alignment: A New Alignment Framework via Test-Time Scaling
Distortion of AI Alignment Revisited: RLHF is a Decent Utilitarian Aligner
General Synthetic-Powered Inference
Learning the Best Under Constraints: A Duality-Based Framework
Pull Requests as a Training Signal for Repo-Level Code Editing
Sign Lock-In: Randomly Initialized Weight Signs Persist and Bottleneck Sub-Bit Model Compression
Linear Ensembles Wash Away Watermarks: On the Fragility of Distributional Perturbations in LLMs
Game-Theoretic Co-Evolution for LLM-Based Heuristic Discovery
Stop the Flip-Flop: Context-Preserving Verification for Fast Revocable Diffusion Decoding
Optimal conversion from Rényi Differential Privacy to $f$-Differential Privacy
Detecting Contextual Hallucinations in Large Language Models with Frequency-Aware Attention
Dynamic Thinking-Token Selection for Efficient Reasoning in Large Reasoning Models
Hamiltonian Asymmetric Fusion: One-Way Safe Directed Refinement under Modality Imbalance
Jailbreaking Vision-Language Models Through the Visual Modality
Sparse Tokens Suffice: Jailbreaking Audio Language Models via Token-Aware Gradient Optimization
Jailbreak to Protect: Buffering Harmful Fine-Tuning via Temporary Jailbreaking LoRA in Large Language Models
Mitigating the Safety–Utility Trade-off in LLM Alignment via Adaptive Safe Context Learning
Diagnosing and Correcting Concept Omission in Multimodal Diffusion Transformers
Acoustic Interference: A New Paradigm Weaponizing Acoustic Latent Semantic for Universal Jailbreak against Large Audio Language Models
From Prompts to Tokens: Internalizing Causal Supervision in Vision-Language Model for Multi-Image Causal Reasoning
Questioning the Coverage-Length Metric in Conformal Prediction: When Shorter Intervals Are Not Better
FedPAT: Federated Test-Time Adaptation via Prototype Affinity Topology
MAS-ProVe: Understanding the Process Verification of Multi-Agent Systems
Dywave: Event-Aligned Dynamic Tokenization for Heterogeneous IoT Sensing Signals
Quantifying and Optimizing Simplicity via Polynomial Representations
MAS-Orchestra: Understanding and Improving Multi-Agent Reasoning Through Holistic Orchestration and Controlled Benchmarks
Forget by Uncertainty: Orthogonal Entropy Unlearning for Quantized Neural Networks
Conditional Clifford-Steerable CNNs for PDE Modeling
AugMask: Score-Based Generative Modeling of Incomplete Tabular Data via Augmentation and Masking
UltraLIF: Fully Differentiable Spiking Neural Networks via Ultradiscretization and Max-Plus Algebra
Reliable Confidence Alignment for Generalized Category Discovery
Dyn-VPP: Video Prediction Policy Optimization for Improved Visual Dynamics
d2p: Fast and Scalable Structured Attention with Differentiable Dynamic Programming
Unlocking Zero-Shot Geospatial Reasoning via Indirect Rewards
ToMoE: Converting Dense Large Language Models to Mixture-of-Experts through Dynamic Structural Pruning
RAD: Retrieval High-quality Demonstrations to Enhance Decision-making
Task-Aware Exploration via a Predictive Bisimulation Metric
Exploring 3D Dataset Pruning
LAGEA: Language Guided Embodied Agents for Robotic Manipulation
Prototype-Grounded Concept Models for Verifiable Concept Alignment
Principled Zero-shot Ranking Agents with Tournament Graphs
GI-GCN: Global Interacted Graph Convolutional Networks via Dominant Sets for Graph Classification
Collaborative and Efficient Fine-tuning: Leveraging Task Similarity
Drift is a Sampling Error: SNR-Aware Power Distributions for Long-Horizon Robotic Planning
FedScar: Correcting Geometric Bias for Flatness-Consistent Federated Learning
ALSO: Adversarial Online Strategy Optimization for Social Agents
ePC: Fast and Deep Predictive Coding for Digital Hardware
Quantitative Estimation of Target Task Performance from Unsupervised Pretext Task in Semi/Self-Supervised Learning
xKV: Cross-Layer KV-Cache Compression via Aligned Singular Vector Extraction
Trading Complexity for Expressivity Through Structured Generalized Linear Token Mixing
Correcting Visual Blur Induced by Attention Distraction to Reduce Hallucinations: Algorithm and Theory
ToaSt: Token Channel Selection and Structured Pruning for Efficient ViT
PruneFuse: Efficient Data Selection via Weight Pruning and Network Fusion
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
Corruption-Tolerant Asynchronous Q-Learning with Near-Optimal Rates
Utonia: Toward One Encoder for All Point Clouds
DDP-WM: Disentangled Dynamics Prediction for Efficient World Models
SALAAD: Sparse And Low-Rank Adaptation via ADMM for Large Language Model Inference
Mitigating Conversational Inertia in Multi-Turn Agents
SlerpFlow: Spherical Trajectory Correction for Rectified Flow Inversion
Learning multi-modal generative models with permutation-invariant encoders and tighter variational objectives
Little By Little: Continual Learning via Incremental Mixture of Rank-1 Associative Memory Experts
Enhancing Reasoning for Diffusion LLMs via Distribution Matching Policy Optimization
ARC-Decode: Accelerated Decoding with Risk-Bounded Acceptance
Improving the Sensitivity of Backdoor Detectors via Class Subspace Orthogonalization
GenExam: A Multidisciplinary Text-to-Image Exam
Transfer Learning in Nonparametric Regression with Deep ReLU Networks
Theoretical Challenges in Learning for Branch-and-Cut
Manifold-Optimal Guidance: A Unified Riemannian Control View of Diffusion Guidance
Efficient Generative Modeling beyond Memoryless Diffusion via Adjoint Schrödinger Bridge Matching
BFTS: Thompson Sampling with Bayesian Additive Regression Trees
GCIB: Graph Contrastive Information Bottleneck for Multi-Behavior Recommendation
Grounding LLMs in Scientific Discovery via Embodied Actions
Large Language Models Explore by Latent Distilling
Evaluating the Representation Space of Diffusion Models via Self-Supervised Principles
Zero-Flow Encoders
VecDesigner: Exploring Visual Guidance and Structural Consistency for Semantic Typography
Minimum Distance Summaries for Robust Neural Posterior Estimation
Learning Coupled Continuous-Time Latent Dynamics from Irregular Events
BiRQA: Bidirectional Robust Quality Assessment for Images
Foreground-Aware Token Routing Vision Transformer for Real-Time Satellite Video Tracking
From Static Constraints to Dynamic Adaptation: Sample-Level Constraint Release for Offline-to-Online Reinforcement Learning
Envisioning Beyond the Few: Disentangled Semantics and Primitives for Few-Shot Atypical Layout-to-Image Generation
VideoFlexTok: Flexible-Length Coarse-to-Fine Video Tokenization
Parameter Manifold Purification
Making Foundation Models Probabilistic via Singular Value Ensembles
CoarseBind: Fast and Accurate Binding Affinity Prediction through Coarse Structural Representations
Multimodal Scaling Laws for Task & Data-Optimized Models of Visual Cortex
Efficient Test-time Inference for Generative Planning Models with OCL Search
FlowPET: Physics-Informed Symplectic Flow Matching for Low-Count PET Reconstruction
Learning on Higher-Order Structures with Effective Operators
Any-Order GPT as Masked Diffusion Model: Decoupling Formulation and Architecture
Advantage Weighted Matching: Aligning RL with Pretraining in Diffusion Models
Both Semantics and Reconstruction Matter: Making Representation Encoders Ready for Text-to-Image Generation and Editing
FlexRank: Nested Low-Rank Knowledge Decomposition for Adaptive Model Deployment
NNiT: Width-Agnostic Neural Network Generation with Structurally Aligned Weight Spaces
Unifying Heterogeneous Degradations: Uncertainty-Aware Diffusion Bridge Model for All-in-One Image Restoration
Toward Training Superintelligent Software Agents through Self-Play SWE-RL
Beyond Rewards in RL for Cyber Defence
SALSA-V: Shortcut-Augmented Long-form Synchronized Audio from Videos
Infinite Mask Diffusion for Few-Step Distillation
Beyond VLM-Based Rewards: Diffusion-Native Latent Reward Modeling
Adversarial Attack and Defense for Denoising Diffusion Sampling
A Kinetic-Energy Perspective of Flow Matching
Mean Flow Distillation: Robust and Stable Distillation for Flow Matching Models
Removing Sandbagging in LLMs by Training with Weak Supervision
Abductive Reasoning with Probabilistic Commonsense
GLAD: Bidirectional Structure-Attribute Alignment via Latent Graph Diffusion Models
Factored Latent Action World Models
Split Personality Training: Revealing Latent Knowledge Through Alternate Personalities
The surprising strength of weak classifiers for validating neural posterior estimates
SWE-Compass: Towards Unified Evaluation of Agentic Coding Abilities for Large Language Models
Diamond Maps: Efficient Reward Alignment via Stochastic Flow Maps
Joint Enhancement and Classification using Coupled Diffusion Models of Signals and Logits
Factored Classifier-Free Guidance
Towards Scalable and Consistent 3D Editing
Position: Stop Chasing the C-index when Evaluating Survival Analysis Models
PortraitRL: Reinforcement Learning for Personalized Portrait Pose Transfer with Multi-Objective Reward Modeling
HSMAD: Heterophily-Driven Spectral and Manifold Learning for Graph Anomaly Detection
Optimization, Generalization and Differential Privacy Bounds for Gradient Descent on Kolmogorov–Arnold Networks
Learning the Interaction Prior for Protein-Protein Interaction Prediction: A Model-Agnostic Approach
On the Robustness of Langevin Dynamics to Score Function Error
AesFormer: Transform Everyday Photos into Beautiful Memories
Position: Beyond Reasoning Zombies — AI Reasoning Requires Process Validity
LaRA-Fusion: Latent-Robust Adaptation via Dual-Loop Constraints for Infrared and Visible Image Fusion
Simple yet Effective: Low-Rank Spatial Attention for Neural Operators
WaterSIC: information-theoretically (near) optimal linear layer quantization
TriAttention: Efficient Long Reasoning with Trigonometric KV Compression
Position: AI Welfare Is Bullshit
Newton-coupled Dual-Teacher Semi-supervised Learning Framework
Self Optimizing Language Models
Structurally Aligned Subtask-Level Memory for Software Engineering Agents
Toward More Reliable Agent Evaluation: A Component-Based Benchmark Auditing Pipeline
Good SFT Optimizes for SFT, Better SFT Prepares for Reinforcement Learning
Near-Optimal Regret for Policy Optimization in Contextual MDPs with General Offline Function Approximation
Reinforcement Learning with Discrete Diffusion Policies for Combinatorial Action Spaces
Exposing Vulnerabilities in Explanation for Time Series Classifiers via Dual-Target Attacks
FLIPS: Instance-Fingerprinting for LLMs via Pseudo-random Sequences
Error Propagation in Dynamic Programming: From Stochastic Control to American Option Pricing
Deterministic Inference across Tensor Parallel Sizes That Eliminates Training-Inference Mismatch
Variational Learning for Insertion-based Generation
Assistive Prompt Mediation: Evaluating Language Models Under Accessibility Constraints
Escaping the Mode: Multi-Answer Reinforcement Learning in LMs
Transport and Merge: Cross-Architecture Merging for Large Language Models
TMS: Trajectory-Mixed Supervision for Reward-Free, On-Policy SFT
On the Separability of Information in Diffusion Models
Less is More: Neuroscience-Motivated Probing for Efficient Concept Circuits Tracing
Self-Supervised Dynamical System Representations for Physiological Time-Series
CATArena: Evaluating Evolutionary Capabilities of Code Agents via Iterative Tournaments
Commit to the Bit: Reactive Reinforcement Learning Done Right
Beyond Accuracy: What Matters in Designing Well-Behaved Image Classification Models?
Clarify Before You Draw: Proactive Agents for Robust Text-to-CAD Generation
Bounded Hyperbolic Tangent: A Stable and Efficient Alternative to Pre-Layer Normalization in Large Language Models
Reliable Thinking with Images
OpenTSLM: Time-Series Language Models for Reasoning over Multivariate Medical Text- and Time-Series Data
The (Marginal) Value of a Search Ad: An Online Causal Framework for Repeated Second-price Auctions
Set Diffusion: Interpolating Token Orderings between Autoregression and Diffusion for Fast and Flexible Decoding
Benchmarking at the Edge of Comprehension
d2: Improved Techniques for Training Reasoning Diffusion Language Models
Selective Deferred Routing: Enabling Cost-Efficient Collaboration between Local SLMs and Remote LLMs
LLawCo: Learning Laws of Cooperation for Modeling Embodied Multi-Agent Behavior
PuzzleMoE: Efficient Compression of Large Mixture-of-Experts Models via Sparse Expert Merging and Bit-packed inference
Expert-guided Clinical Text Augmentation via Query-Based Model Collaboration
The Labyrinth and the Thread: Rethinking Regularizations in Sequential Knowledge Editing for Large Language Models
AI Engram: In Search of Memory Traces in Artificial Intelligence
MemIncept: Steering LLM Agents via Cooperative Stealthy Memory Injections
Bio-Inspired Self-Supervised Learning for Wrist-worn IMU Signals
HERMES: Towards Efficient and Verifiable Mathematical Reasoning in LLMs
Leveraging Evidence Priors for Robust Prompt Learning under Noisy Supervision in Vision-Language Models
From Out-of-Distribution Detection to Hallucination Detection: A Geometric View
E-VAds: An E-commerce Short Videos Understanding Benchmark for MLLMs
Reasoning Cache: Learning to Extrapolate to Long Lengths via Short-Length RL
Reasoning Models Are Test Exploiters: Rethinking Multiple Choice
RoCA: Robust Cross-Domain End-to-End Autonomous Driving
GIST: Targeted Data Selection for Instruction Tuning via Coupled Optimization Geometry
Language Models as Nodes: Constructing a High-Level Neural Network
LOCA-bench: Benchmarking Language Agents Under Controllable and Extreme Context Growth
Attention Hijacking: Backdooring Text Dataset Distillation via Semantic Anchors
CLAA: Cross-Layer Attention Aggregation for Accelerating LLM Prefill
Empirical Gaussian Processes
DynaSchedBench: Calibrated Dynamic Scheduling Benchmarks and Observability Paradox in LLM-based Scheduling Agents
Anytime-Valid Inference for Online Ranking of Large Language Models
Understanding Reasoning Collapse in LLM Agent Reinforcement Learning
A Theoretical Framework for Modular Learning of Robust Generative Models
TapSampling: Inference-Time Sampling with a Task-Progress-Understanding Verifier for Robotic Manipulation
Generalized Discrete Diffusion with Self-Correction
TEAM: Temporal–Spatial Consistency Guided Expert Activation for MoE Diffusion Language Model Acceleration
Detecting Errors in AI-Generated Annotations: When and Why Semantic Neighbors Help
Unbiased Principles, Robust Rewards
MoSE: Mixture of Slimmable Experts for Efficient and Adaptive Language Models
ArborKV: Structure-Aware KV Cache Management for Scaling Tree-based LLM Reasoning
CodeChemist: Test-Time Scaling for Low-Resource Code Generation via Functional Knowledge Transfer
Efficient Multi-modal Dataset Distillation via Analytic Parameter Matching
FT-Dojo: Towards Autonomous LLM Fine-Tuning with Language Agents
TimeLAVA: Learning-Agnostic Valuation for Time Series Data
Adaptive Reinforcement Learning for Unobservable Random Delays
What If We Allocate Test-Time Compute Adaptively?
PASA: A Principled Embedding-Space Watermarking Approach for LLM-Generated Text under Semantic-Invariant Attacks
Convex Basins in Single-Index Model Loss Landscapes: Applications to Robust Recovery under Strong Adversarial Corruption
Cram Less to Fit More: Training Data Pruning Improves Memorization of Facts
GeoPT: Scaling Physics Simulation via Lifted Geometric Pre-Training
Agent-Omit: Training Efficient LLM Agents for Adaptive Thought and Observation Omission via Agentic Reinforcement Learning
SafeCompass: Dynamic Chain-of-Thought Steering via Inference-Time Safety Signals
Cold-Start Personalization via Training-Free Priors from Structured World Models
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
EchoingPixels: Aliasing-Resistant Joint Token Reduction for Audio-Visual LLMs
MIND: Decoupling Model-Induced Label Noise via Latent Manifold Disentanglement
LILO: Bayesian Optimization with Natural Language Feedback
RealtimeTool: Parallel Decoding for Real-Time LLM Function Calling
GradMem: Learning to Write Context into Memory with Test-Time Gradient Descent
No Retraining at Edge: Efficient Resource-Aware Mixed-Precision Quantization via Federated Supernet Learning
CausalX: A Unified and Causally-Interpretable Plug-and-Play Model for Multi-modal Spatio-Temporal Forecasting
PinTok: Tokenizers Deserve Dedicated Pinned CPU-Compute and Memory
DuFal: Dual-Frequency-Aware Learning for High-Fidelity Extremely Sparse-view CBCT Reconstruction
DyLLM: Efficient Diffusion LLM inference via saliency-based token selection and partial attention
HiMAP-Travel: Hierarchical Multi-Agent Planning for Long-Horizon Constrained Travel
Knowing Bias, Doing Better: Mitigating Social Bias in LLMs via Know-Bias Neuron Enhancement
Automatic Layer Selection for Hallucination Detection
Universal One-third Time Scaling in Learning Peaked Distributions
Rethinking Parameter Sharing as Graph Coloring for Structured Compression
ROAMM: A Benchmark Dataset for Multimodal Human Attention Decoding and EEG-to-Text Modeling During Naturalistic Reading
Intervene When It Doubts: Conjunction-Guided Interactive Reasoning
Logit-Attention Divergence: Mitigating Position Bias in Multi-Image Retrieval via Attention-Guided Calibration
NBCG: Nash-Bargained Causal Game for Long-Tailed Multi-Label NLP
Failure-Driven Workflow Refinement
VR-Thinker: Boosting Multimodal Reward Models through Think with Image Reasoning
Progressive Cramming: Reliable Token Compression and What It Reveals
SOLAR for Offline MARL: Plateau-Triggered Potential Shaping under World-Model Uncertainty
TraCeS: Learning Per-Timestep Constraint-Violation Credit from Sparse Trajectory-Level Labels
Criterion-Conditional In-Context Learning: Evaluating Criterion-Shift Adaptation in Vision-Language Models
Riemannian Generative Decoder
Batch Normalization for Neural Networks on Complex Domains
Gromov-Wasserstein at Scale, Beyond Squared Norms
Smoothing Slot Attention Iterations and Recurrences
Online Fair Division with Additional Information
Approximate Proportionality in Online Fair Division
Detached Skip-Links and $R$-Probe: Decoupling Feature Aggregation from Gradient Propagation for MLLM OCR
Fix the Loss, Not the Radius: Rethinking the Adversarial Perturbation of Sharpness-Aware Minimization
Sufficiency is Relative: Evaluating LLM Explanations under Model-Induced Input Distributions
Function-Valued Causal Influence in Nonlinear Time Series
Parameter-free Dynamic Regret: Time-varying Movement Costs, Delayed Feedback, and Memory
Position: Topological Machine Learning Cannot Progress without Experimental Standards
Towards Fine-grained Robustness: Attention-guided Test-time Prompt Tuning for Vision-Language Models
Real-Time Monitoring and Calibration of Chain-of-Thought Sycophancy in Large Reasoning Models
Causal Structure Learning for Sparse Matrix Fill-in Reduction
Directional Neural Collapse for Self-Supervised Visual Representation Learning
IdEst: Assessing Self-Supervised Learning Representations via Intrinsic Dimension
Doppler Prompting for Stable mmWave-based Human Pose Estimation
Parallel Stochastic Gradient-Based Planning for World Models
From Denoising to De-Channeling: Integrating Physical Channel Priors into Diffusion Models for Radio Signal Understanding
Topology-Aware Contrastive Learning: Regulating Representation Connectivity via Persistent Homology
Interpretable Self-Supervised Learning via Representer Landmarks and Nyström Approximation
Protein Circuit Tracing via Cross-layer Transcoders
Rethinking Temporal Consistency in Video Object-Centric Learning: From Prediction to Correspondence
TSRBench: A Comprehensive Multi-task Multi-modal Time Series Reasoning Benchmark for Generalist Models
Tracking Drift: Variation-Aware Entropy Scheduling for Non-Stationary Reinforcement Learning
VJEPA: Variational Joint Embedding Predictive Architectures as Probabilistic World Models
Var-JEPA: Variational Joint-Embedding Predictive Architecture – Bridging Predictive and Generative Self-Supervised Learning
Imitation Learning for Multi-turn LM Agents via On-policy Expert Corrections
Can Agents Generalize to the Open World? Unveiling the Fragility of Static Training in Tool Use
Efficient, Property-Aligned Fan-Out Retrieval via RL-Amortized Diffusion
Semantic-level Backdoor Attack against Text-to-Image Diffusion Models
Fedfit: Federated dynamic pruning via Fisher Information scoring
On the Accuracy of Newton Step and Influence Function Data Attributions
CRAMER: Control via Request-Aware Masking for Editing Recommenders
Perceptrons and Localization of Attention’s Mean-Field Landscape
DenseMLLM: Standard Multimodal LLMs are Intrinsic Dense Predictors
Score Based Error Correcting Code Decoder
On the Provable Suboptimality of Momentum SGD in Nonstationary Stochastic Optimization
Gradient-Based Causal Tree Ensembles: A Backbone Architecture for Heterogeneous Treatment Effects
Better, Faster: Harnessing Self-Improvement in Large Reasoning Models
Improved Convergence Analysis of Topology Dependence in Decentralized SGD
Protein Autoregressive Modeling via Multiscale Structure Generation
Variational inference via Gaussian interacting particles in the Bures-Wasserstein geometry
Safety Alignment of LMs via Non-cooperative Games
DNACHUNKER: Learnable Tokenization for DNA Language Models
Active Tabular Augmentation via Policy-Guided Diffusion Inpainting
Beyond Unidirectional Bias: Reciprocal Perspective Calibration in Scene Graph Generation
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
Covariance Volume Maximization for Embodied Latent Exploration in Deep Reinforcement Learning
RouteFinder: Towards Foundation Models for Vehicle Routing Problems
Hugging Carbon: Quantifying the Training Carbon Emissions of AI Models at Scale
Smooth Dynamic Cutoffs for Machine Learning Interatomic Potentials
Explaining Concept Shift with Interpretable Feature Attribution
The Latent Guardian: Defending Collaborative Perception via Feature-Level Consistency Verification
Scaling Laws and Architectural Frontiers in Metagenomic Foundation Models
OvisOCR: End-to-End Document Parsing via Aligning Specialized Perception with General Reasoning
Distributional Open-Ended Evaluation of LLM Cultural Value Alignment Based on Value Codebook
Position: Generative Engine Optimization Creates Underexamined Risks, Governance Must Target Concentration, Disclosure, and Academic Blind Spots
GDPO: Group reward-Decoupled Normalization Policy Optimization for Multi-reward RL Optimization
ToolOrchestra: Elevating Intelligence via Efficient Model and Tool Orchestration
Speculative Sampling For Faster Molecular Dynamics
MAST: Motif-Augmented Diffusion with Search Tree for Spectroscopic Molecular Structure Elucidation
Protein Design with Agent Rosetta: A Case Study for Specialized Scientific Agents
MetaDNS: Enhancing Exploration in Discrete Neural Samplers via Metadynamics
Structure-Preserving Learning Improves Geometry Generalization in Neural PDEs
From Human Labels to Literature: Semi-Supervised Learning of NMR Chemical Shifts at Scale
Efficient and Safe Molecular Assembly via Reinforcement Learning and Constraint Solving
Hermite-NGP: Gradient-Augmented Hash Encoding for Learning PDEs
Large-Scale Molecular Dynamics Simulations: Direct Interatomic Modeling with Dilated Message Passing
ReViT: Rotational-equivariant Vision Transformers for Neural PDE Solvers
Multiview Self-Representation Learning across Heterogeneous Views
FlexiFlow: decomposable flow matching for generation of flexible molecular ensemble
From Holo Pockets to Electron Density: GPT-style Drug Design with Density
Learning Compressed Shape-Aware Molecular Representations for Virtual Screening
MOES-Pred: Molecular Structural Representation Learning by Adaptive Energy-Sentinel Vibration for Generalized Property Prediction
Tighter Regret Lower Bound for Gaussian Process Bandits with Squared Exponential Kernel in Hypersphere
Norm$\times$Direction: Restoring the Missing Query Norm in Vision Linear Attention
OSM+: Billion-Level Open Street Map Dataset for City-wide Experiments
Finding the Minimal Parameter Budget for Implicit Reasoning: A Data Complexity Driven Scaling Law for Language Models
SynLaD: Latent Diffusion for Generating Synthesizable Molecules Conditioned on 3D Pharmacophore Profiles
VideoSEG-O3: A Multi-turn Reinforcement Learning Framework for Reasoning Video Object Segmentation
Breaking the Block: Preserving Data Continuity to Train Superior SAEs for Instruct Models
IRIS: Implicit Reward-Guided Internal Sifting for Mitigating Multimodal Hallucination
Mitigating Visual Hallucinations via Semantic Curriculum Preference Optimization in MLLMs
MICE-Bench: A Challenging and Comprehensive Benchmark for Multi-Reference Image Creation and Editing
MoSSP: A Momentum-Based Single-Loop Stochastic Penalty Method for Nonconvex Constrained DC Optimization
ChartE$^{3}$: A Comprehensive Benchmark for End-to-End Chart Editing
UFO: Chain-of-Evaluation for Omni-Condition Alignment in Multi-Modal Image Generation
TestExplora: Benchmarking LLMs for Proactive Bug Discovery via Repository-Level Test Generation
MiVE: Multiscale Vision-language features for reference-guided video Editing
3DPoV: Improving 3D understanding via Patch Ordering on Videos
SleepMaMi: A Universal Sleep Foundation Model for Integrating Macro- and Micro-structures
PyVision-RL: Forging Open Agentic Vision Models via RL
World-Shaper: A Unified Framework for 360° Panoramic Editing
Interactive Segmentation with Elaborate Focus Prior
ArcVQ-VAE: A Spherical Vector Quantization Framework with ArcCosine Additive Margin
SPEED: Sharpened-Teacher Distillation for Parallel Decoding of Diffusion Language Models
Divide-and-Denoise: A Game-Theoretic Method for Fairly Composing Diffusion Models
CLEAR: Context-Aware Learning with End-to-End Mask-Free Inference for Adaptive Subtitle Removal
Learning More from Less: Unlocking Internal Representations for Benchmark Compression
ReaForest: Fostering Generative Video Reasoning for Spatial Planning
Rethinking Serialization in Linear 3D Vision: Decoupling Anisotropic Geometry from Isotropic Semantics
nD-RoPE: A Generalized RoPE for n-Dimensional Position Embedding
Continual Learning With Participation Privacy: An Auditable Buffering-Aggregation Recipe
DAL: A Practical Prior-Free Black-Box Framework for Piecewise Stationary Bandits
PSBench: Editing Image via GUI Agents in Photoshop
From Reasoning Traces to Reusable Modules: Reinforcement Learning for Compositional Generalization in Language Model Reasoning
VideoSEAL: Separating Planning from Answer Authority for Agentic Long Video Understanding
HieRD: Hierarchical Relational Distillation for Vision-Language Embedding Models
Robust Signal Enhancement via Fractional Detail Views and Knowledge Guided Multi-view Fusion
ProAct: A Benchmark and Multimodal Framework for Structure-Aware Proactive Response
ForensicConcept:Transferable Forensic Concepts for AIGI Detection
GRASP: Awakening Latent Spatial Reasoning in LVLMs via Training-free Geometric Rectification
Active Regression for Single-Index Models with Unknown Link Functions
Continuity-Regularized Flow Matching for Offline Reinforcement Learning
Reward-Preserving Counterfactual State Editing for Offline Reinforcement Learning
When Generalized Zero-Shot Learning Meets PU Learning: A Plug-and-Play Framework for Seen-Class Bias Mitigation
Real-Time and Lightweight Diffusion Image Compression
Move-Then-Operate: Behavioral Phasing for Human-Like Robotic Manipulation
iVGR: Internalizing Visually Grounded Reasoning for MLLMs with Reinforcement Learning
Must All Negatives Be Pushed Away Equally? Uncertainty-Aware Cross-View Geo-Localization via Normal Inverse Gamma Distribution
GUI-Spotlight: Adaptive Iterative Focus Refinement for Enhanced GUI Visual Grounding
TreePO: Enhancing Policy Efficacy and Inference Efficiency with Tree Modeling
Distillation Models are Good Samplers for Diffusion Reinforcement Learning
WEVSR: Adapting Video Diffusion Generators to Real-World Video Super‑Resolution with Wavelet-Enhanced VAE Encoder
VideoKR: Towards Knowledge- and Reasoning-Intensive Video Understanding
Hide&Seek: Learning to explain in an end-to-end differentiable network
Verbalized Sampling: How to Mitigate Mode Collapse and Unlock LLM Diversity
Proteus: Lookup-Free Trellis-Coded Quantization by Lattice-Breaking Compute Codes for 2-Bit LLMs
Dichotomy of Feature Learning and Unlearning: Fast-Slow Analysis on Neural Networks with Stochastic Gradient Descent
Words & Weights: Streamlining Multi-Turn Interactions via Co-Adaptation
LSGQuant: Layer-Sensitivity Guided Quantization for One-Step Diffusion Real-World Video Super-Resolution
Alterbute: Editing Intrinsic Attributes of Objects in Images
CamGeo: Sparse Camera-Conditioned Image-to-Video Generation with 3D Geometry Priors
When Shared Knowledge Hurts: Spectral Over-Accumulation in Model Merging
Recovering Hidden Reward in Diffusion-Based Policies
Unveiling Multi-regime Patterns in SciML: Distinct Failure Modes and Regime-specific Optimization
Beyond Confidence: Adaptive and Coherent Decoding for Diffusion Language Models
Unsafer in Many Turns: Benchmarking and Defending Multi-Turn Safety Risks in Tool-Using Agents
TSMGen: Target-Specific Molecule Generation via Higher-Order Structural Dependencies and Context-Aware Bidirectional Fusion
TexEditor: Structure-Preserving Text-Driven texture Editing
CSD: Content-aware Speculative Decoding for Efficient Image Generation
EARL: Towards a Unified Analysis-Guided Reinforcement Learning Framework for Egocentric Interaction Reasoning and Pixel Grounding
Self-Prompting Diffusion Transformer for Open-Vocabulary Scene Text Edit via In-Context Learning
Class-Prior Perturbation-Robust Regularization for Imbalanced Unreliable Partial Label Learning
Position: Stop Using Culturally Biased Human Cognitive Benchmarks to Evaluate LLMs
EgoTactile: Learning Grasp Pressure for Everyday Objects from Egocentric Video
StableI2I: Spotting Unintended Changes in Image-to-Image Transition
Motion-Residual Conflict-Aware Time Reversal for Generative Inbetweening
ProOPF: Benchmarking and Improving LLMs for Professional-Grade Power Systems Optimization Modeling
Towards Parameter-Free Temporal Difference Learning
APEX: Approximate-but-exhaustive search for ultra-large combinatorial synthesis libraries
RiboSphere: Learning Unified and Efficient Representations of RNA Structures
Explicit representation of germline and non-germline residues improves antibody language modeling
Any3D-VLA: Enhancing VLA Robustness via Diverse Point Clouds
Vegas: Self-Speculative Decoding with Verification-Guided Sparse Attention
Learning to Reason for Factuality
Physiology-Aware Masked Cross-Modal Reconstruction for Biosignal Representation Learning
Discontinuous Galerkin Neural Operator for Pathology Defocus Deblurring
Adaptive Protein Tokenization
Structure-Aware Riemannian Flow Matching for Registration and Fusion of Hyperspectral and Multispectral Images
HybridFlow: Resource-Adaptive Subtask Routing for Efficient Edge-Cloud LLM Inference
Physiology as Language: Translating Nocturnal Breathing to EEG
Adaptive DNA Sequence Modeling via Synergistic Plasticity Units
Spherical Procrustes Alignment for Reliable Medical Audio Diagnosis
Capacity without Access: Reinterpreting the Mid-Depth Spectral Plateau in LLMs
ECG-R1: Protocol-Guided and Modality-Agnostic MLLM for Reliable ECG Interpretation
Enhancing Protein-Protein Interaction Prediction with Hierarchical Motif-based Multimodal Protein Embedding
UOTIP: Unbalanced Optimal Transport Map for Unpaired Inverse Problems
SGERA: Stein-Guided ECG-Report Alignment for ECG Representation Learning
Reference-Free Meta-Learning for Generalized Implicit Neural Representation in Efficient MRI Reconstruction
HDTree: Generative Modeling of Cellular Hierarchies for Robust Lineage Inference
HEARTS: Benchmarking LLM Reasoning on Health Time Series
A Regime-Aware Trajectory Prediction Framework for 1000+ Systems Biology Models
Proactive Defense Benchmark against Deepfake Generation
DistMatch: Adaptive Binning via Distribution Matching for Robust Sequential Conformal Prediction
EpiTwin: Spatiotemporal Graph Transformers for Epileptic sEEG Signal Reconstruction
Who Evaluates AI's Social Impacts? Mapping Coverage and Gaps in First and Third Party Evaluations
Stable-GFlowNet: Toward Diverse and Robust LLM Red-Teaming via Contrastive Trajectory Balance
Noise Tectonics: Measuring the Stability of AI Benchmark Ecosystems
WorldTravel: A Realistic Multimodal Travel-Planning Benchmark with Tightly Coupled Constraints
LiveFigure: Generating Editable Scientific Illustration with VLM Agents
AgentSteerTTS: A Multi-Agent Closed-Loop Framework for Composite-Instruction Text-to-Speech
Can local learning match self-supervised backpropagation?
Online Tensor Learning: Computational and Statistical Trade-offs, Adaptivity and Optimal Regret
How do Human Processes AI-generated Hallucination Contents: a Neuroimaging Study
Formalizing the Binding Problem
Learning Biophysical Models of Large-Scale Multineuronal Data To Enable Precise Neurostimulation
Memory-Distilled Selection for Noise-Robust Anomaly Detection
Deep Progressive Training: scaling up depth capacity of zero/one-layer models
Towards Whole-corpus Reconstruction of Heterogeneous RAG Knowledge Bases
Sampling and Identity-Testing Without Approximate Tensorization of Entropy
The Art of Interrogation: Consistency Amplifies Factuality in Spatial Reasoning
Mixtures Closest To A Given Measure: A Semidefinite Programming Approach
Nonlinear Covariate Balance in Experimental Design
CLINIC: Towards High-quality Graph Out-Of-Distribution Detection
A Conflict-aware Evidential Framework for Reliable Sleep Stage Classification
Decompose and Recompose: Reasoning New Skills from Existing Abilities for Cross-Task Robotic Manipulation
MSP: Probabilistically Consistent Multi-Scale Action Generation
VLA-Arena: An Open-Source Framework for Benchmarking Vision-Language-Action Models
Factorized Scheduling Principle: Learning Interpretable and Transferable Policies via Structured Additive Functions
When Actions Go Off-Task: Detecting and Correcting Misaligned Actions in Computer-Use Agents
Eating for a Sustainable Planet: Personalized Sustainable Diet Recommendation via Constraint-Aware Decision-Making Modeling
Dirichlet-Prior Shaping: Guiding Expert Specialization in Upcycled MoEs
Towards a Unified Generative Model for Scarce Time Series with Domain Experts
When Drafts Evolve: Speculative Decoding Meets Online Learning
Interpreting Physics in Video World Models
At the Edge of Understanding: Sparse Autoencoders Trace The Limits of Transformer Generalization
Decoupling Universal Laws and Environmental Heterogeneity: A Physics-Inspired Framework for Robust Spatio-Temporal Forecasting
Weaving in the Clouds: Achieving Synergistic Collaboration among LLM Agents via Federated Learning
TokSuite: Measuring the Impact of Tokenizer Choice on Language Model Behavior
Exploring Motif-based Heterogeneous Graph Learning for ReDoS Detection
Can We Build a Monolithic Model for Fake Image Detection? SICA: Semantic-Induced Constrained Adaptation for Unified-Yet-Discriminative Artifact Feature Space Reconstruction
Finding DoRI: Discovery of Retained Images in Diffusion Models
Euclean: Automated Geometry Problem Formalization with Unified Verification in Lean
PACEAttention: Principled and Adaptive Feature Compression-Expansion Grounded in the Geometry of $\text{MCR}^2$
EnterpriseOps-Gym: Environments and Evaluations for Stateful Agentic Planning and Tool Use in Enterprise Settings
CoME: Empowering Channel-of-Mobile-Experts with Informative Hybrid-Capabilities Reasoning
Target-Driven Policy Optimization for Sequential Counterfactual Outcome Control
A Systematic Study of Behavioral Cloning for Scientific Data Annotation
Can Recommender Systems Teach Themselves? A Recursive Self-Improving Framework with Fidelity Control
LLM-Guided Loop Bound Generation for Program Termination Verification
Expert-level Leaf Cell Layout Generation via Preference-Optimized LLM
Pareto-Guided Optimal Transport for Multi-Reward Alignment
1-Bit Wonder: Improving QAT Performance in the Low-Bit Regime through K-Means Quantization
Auto-regressive In-context Demonstration Selection
Autoregressive Direct Preference Optimization
Position: The Alignment Community is Unintentionally Building a Censor’s Toolkit
Revisiting Distribution Correction Estimation for Offline Imitation Learning with Suboptimal Dataset
LightningRL: Breaking the Accuracy–Parallelism Trade-off of Block-wise dLLMs via Reinforcement Learning
Multi-timescale Reinforcement Learning by Value Reconstruction
Revisiting Photometric Ambiguity for Accurate Gaussian-Splatting Surface Reconstruction
SRPO: Self-Reflective Policy Optimization for Long-Horizon Reasoning
Test-Time Reinforcement Learning for Flow Matching
ASAP: Exploiting the Satisficing Generalization Edge in Neural Combinatorial Optimization
Persuasive Privacy
Group Distributionally Robust Optimization-Driven RL for LLM Reasoning
A Tale of Two Graphs: Separating Knowledge Exploration from Outline Structure for Open-Ended Deep Research
The Surprising Difficulty of Search in Model-Based Reinforcement Learning
Stabilizing PPO via Latent-Space Regularization and KDE-Driven Exploration
Safety Generalization Under Distribution Shift in Safe Reinforcement Learning: A Diabetes Testbed
Langevin Rollout Optimization for Modelic Reinforcement Learning
Randomized Advantage Transformation (RAT): Computing Natural Policy Gradients via Direct Backpropagation
LumiNet: Perception-Driven Knowledge Distillation via Statistical Logit Calibration
Last-Iterate Convergence of Regularized Gradient Methods for Stochastic Monotone Variational Inequalities
AC-ODM: Actor–Critic Online Data Mixing for Sample-Efficient LLM Pretraining
Goal-Conditioned Agents that Learn Everything All at Once
Asymmetric Perturbation in Solving Bilinear Saddle-Point Optimization
Plan, Decouple, Assimilate: Physics-Aware Object Insertion in Remote Sensing Imagery
PAWS: Preference Learning with Advantage-Weighted Segments
Adversarial Latent Embedding Repair for LLM Continual Learning
MobileFusion: Mobile-Friendly Infrared and Visible Image Fusion via Structural Re-parameterization
scDEBART: Predicting in silico Single-Cell Perturbation Responses via Large-Scale Differential Expression Learning
Global Policy-Space Response Oracles for Two-Player Zero-Sum Games
Empty Shelves or Lost Keys? Recall Is the Bottleneck for Parametric Factuality
h1: Bootstrapping LLMs to Reason over Longer Horizons via Reinforcement Learning
Rubric Curriculum RL: Exploiting the Generation-Verification Gap in Creative Writing
Sample-Efficient Diffusion-based Reinforcement Learning with Critic Guidance
UHR-BAT: Budget-Aware Token Compression Vision-Language model for Ultra-High-Resolution Remote Sensing
Single-Rollout Hidden-State Dynamics for Training-Free RLVR Data Selection
Regret Pre-training: Bridging Prior and Posterior Views for Enhanced Knowledge Grounding
RaGEP: Rank-aware Geometric Expert Pruning for Mixture-of-Experts Language Models
ALAS: Additive Learnable Alpha-Stable Kernels for Flexible Bayesian Optimization
CoPE: A Framework for Optimizing Coordination between Planning and Execution in LLM-based Agents
From Distribution to Geometry: Stable Graph Generalization via Invariant Barycenters
Baguan-TS: dual in-context learning model for time series forecasting with covariates
Seg-ReSearch: Segmentation with Interleaved Reasoning and External Search
Fisher-Preserving Guidance: Training-Free Manifold Constraints for Safe Diffusion Control
Functional building blocks of neural networks: from network motifs to collective dynamics
HyMTRL: A Hybrid Multi-Task Reinforcement Learning Framework via Phased Policy Evolution
Reparameterization Proximal Policy Optimization
Quantifying the noise sensitivity of the Wasserstein metric for images
AdaRoPE: Not All Attention Heads Should Rotate and Scale Equally
Improved Bounds for Reward-Agnostic and Reward-Free Exploration
CoGenCast: A Coupled Autoregressive–Flow Generative Framework for Time Series Forecasting
Do Neural Operators Forget Geometry? The Forgetting Hypothesis in Deep Operator Learning
From Knowledge to Inference: Formalizing Specialized Public Health Reasoning on GlobalHealthAtlas
ACTIVE-o3 : Empowering MLLMs with Active Perception via Pure Reinforcement Learning
Trojan-Speak: Bypassing Constitutional Classifiers with No Jailbreak Tax via Adversarial Finetuning
OpenSage: Self-programming Agent Generation Engine
Rethinking Human Intent to CAD: Parametric CAD Model Generation via Cooperative Multi-Task Alignment and Spatial-Aware Reinforcement Learning
Masked Multi-path Contrast with Confidence-Gated Semantic Imputation for Incomplete Multi-view Clustering
Judging What We Cannot Solve: A Consequence-Based Approach for Oracle-Free Evaluation of Research-Level Math
IDRBench: Understanding the Capability of Large Language Models on Interdisciplinary Research
CONTEXTOR: Contextualized High-order Contrastive Learning
TMD-Bench: A Multi-Level Evaluation Paradigm for Music–Dance Co-Generation
PODiff: Latent Diffusion in Proper Orthogonal Decomposition Space for Scientific Super-Resolution
MemCast: Memory-Driven Time Series Forecasting with Experience-Conditioned Reasoning
MindFlow: Mind Supernet Powered Thinking Flows for Research Idea Innovation
Training-Free Hashing-Based Attention via Binary Principal Components
Neuro-evolutionary Continual Reinforcement Learning
Deterministic Component Mining for Multi-framework UI2Code Generation
Induction Meets Biology: Mechanisms of Repeat Detection in Protein Language Models
Progressive Graph Structure Adjustment for Homophily Shift Adaptation
Multilingual Unlearning in LLMs: Transfer, Dynamics, and Reversibility
Query-efficient model evaluation using cached responses
Language Model Circuits Are Sparse in the Neuron Basis
Optimizing Few-Step Generation with Adaptive Matching Distillation
IndexMem: Learned KV-Cache Eviction with Latent Memory for Long-Context LLM Inference
The Signal is in the Steps: Local Scoring for Reasoning Data Selection
CodeClash: Benchmarking Goal-Oriented Software Engineering
MA$^3$S: Model-Agnostic Active Annotation Strategy for Crowdsourcing
FLIP2: Expanding Protein Fitness Landscape Benchmarks for Real-World Machine Learning Applications
When Is Symbolic Regression Tractable?
The Devil is in the Spectrum: Mitigating Representation Collapse in LLMs via Topologically Regularized Side-Path
Rotation-Invariant Spherical Watermarking via Third-Order SO(3) Representation Coupling
Native Parallel Reasoner: Reasoning in Parallelism via Self-Distilled Reinforcement Learning
BabyVision: Visual Reasoning Beyond Language
Comp-Attn: Present-and-Align Attention for Compositional Video Genneration
DLM-Scope: Mechanistic Interpretability of Diffusion Language Models via Sparse Autoencoders
CL-GCL: Comprehensive and Lightweight Graph Contrastive Learning
BioDynaSpec: Harmonic-Guided Spatio-Spectral Autoregressive Diffusion for Protein Dynamics Generation
BrainJanus: A Foundation Model for Unified Understanding and Generation across Brain, Vision, and Language
$\texttt{FlashSchNet}$: Fast and Accurate Coarse-Grained Neural Network Molecular Dynamics
T-GINEE: A Tensor-Based Multi-Graph Representation Learning
CyberCycle: Scalable Real-World Benchmark for AI Agents' End-to-End Cybersecurity Capabilities
TQL: Scaling Q-Functions with Transformers by Preventing Attention Collapse
Differentiable Optimization Layers for Guaranteed Fairness in Deep Learning
Aggregate Models, Not Explanations: Improving Feature Importance Estimation
WorldCompass: Reinforcement Learning for Long-Horizon World Models
WorldPlay: Towards Long-Term Geometric Consistency for Real-Time Interactive World Modeling
FineFocus: Benchmarking and Improving Fine-Grained Text-to-Image Alignment via Paired Reinforcement Learning
ANTiC: Adaptive Neural Temporal In Situ Compressor
MoCo-EA: Exploiting Adversarial Mode Connectivity for Efficient Evolutionary Attacks
NL2Repo-Bench: Towards Long-Horizon Repository Generation Evaluation of Coding Agents
GeoMoLa: Geometry-Aware Motion Latents for Learning Robust Manipulation Policies
Curriculum Reinforcement Learning for Black-Box Prompt Tuning via Large Language Models
Demystifying LLM-as-a-Judge: Analytically Tractable Model for Inference-Time Scaling
Preconditioning Neural Tangent Kernel for Adaptive Optimization
The Implicit Bias of Adam and Muon on Smooth Homogeneous Neural Networks
Reasoning about Reasoning: BAPO Bounds on Chain-of-Thought Token Complexity in LLMs
Overthinking: Amplifying Reasoning Weights to Extract Learned Secrets
Likelihood Matching for Diffusion Models
A Framework for Understanding Learnability in Transformers
CAST: Modeling Visual State Transitions for Consistent Video Retrieval
Muon in Associative Memory Learning: Training Dynamics and Scaling Laws
The Expressivity Limits of Transformers
General Quantification of Covariate and Concept Shifts
Dual Latent Memory for Visual Multi-agent System
TiMi: Empower Time Series Transformers with Multimodal Mixture of Experts
Provable Benefits of RLVR over SFT for Reasoning Models: Learning to Backtrack Efficiently
The Information Geometry of Softmax: Probing and Steering
Contextual Slate GLM Bandits with Limited Adaptivity
Time-CoT: Hierarchical Reasoning with Temporal Semantic Codes for Multivariate Time Series Classification
Reading the Cell, Designing the Cure: Perturbation-Conditioned Molecular Diffusion for Function-Oriented Drug Design
Decentralized Online Convex Optimization with Efficient Communication: Improved Algorithm and Lower Bounds
Best-of-Both-Worlds for Heavy-Tailed Markov Decision Processes
Statistically Undetectable Backdoors in Deep Neural Networks
Belief Propagation Converges to Gaussian Distributions in Sparsely-Connected Factor Graphs
Fair Transit Stop Placement: A Clustering Perspective and Beyond
Calibrated Preference Learning: The Case of Label Ranking
Corrected Samplers for Discrete Flow Models
CauSciBench: Evaluating LLM Causal Inference for Scientific Research
Mirror Descent Policy Optimisation for Robust Constrained Markov Decision Processes
Learning to Correct: Reinforcement Learning for Multi-Attempt Chain-of-Thought
Convergence of Two-Timescale Stochastic Approximation with Markovian Samples and Applications in Reinforcement Learning
Local Hessian Spectral Filtering for Robust Intrinsic Dimension Estimation
Chebyshev Policies and the Mountain Car Problem: Reinforcement Learning for Low-dimensional Control Tasks
d3LLM: Ultra-Fast Diffusion LLM using Pseudo-Trajectory Distillation
FIDIA: Function-Informed Sequence Design via Inference-Aligned Policy Optimization
Secure Multi-agent Reinforcement Learning for Service Systems with Affinity and Byzantine Nodes: Stability Analysis and Protection Design
DistFlow: A Fully Distributed RL Framework for Scalable and Efficient LLM Post-Training
Rethinking GNNs and Missing Features: Challenges, Evaluation and a Robust Solution
Asymmetric Multi-View Clustering with Hyperbolic Uncertainty Modeling
CoPE: Continual Probe-guided Expansion for Large Vision-Language Models
MDGMIX: Boundary-Aware Subgraph Mixing for Multi-Domain Graph Pre-Training
Stochastic Linear Bandits with Parameter Noise
Tri-Scale Neural ODEs for Continuous Multi-Omics Disease Modeling
Multi-Objective Protein Design via Memory-Aware Test-Time Scaling in Diffusion Models
LineageFlow: Flow Matching for High-Fidelity Family-Aware Protein Sequence Generation
Veda: Scalable Video Diffusion via Distilled Sparse Attention
Flash-VAED: Plug-and-Play VAE Decoders for Efficient Video Generation
Breaking the Computational Barrier: Provably Efficient Actor–Critic for Low-Rank MDPs
Consistency Deep Equilibrium Models
ANCHOR: Abductive Network Construction with Hierarchical Orchestration for Reliable Probability Inference in Large Language Models
LMCleaner: Efficient and Certified Online Unlearning via Influence Propagation Truncation
Broadening the Backdoor Basin: Understanding LLM Backdoors Collapse and Making Backdoors Persistent
UniDrag: Unified Multi-Field Prediction and Robust Shape Optimization for Vehicle Aerodynamics
Semi-knockoffs: a model-agnostic conditional independence testing method with finite-sample guarantees
Innovation: An Almost Characterization of Hallucination
Probably Approximately Correct Labels
Characterizing Agents in Production
Deep Pre-Alignment for VLMs
Position: Privacy Is a Claim, Not a Property of Synthetic Data
Robust AI Evaluation through Maximal Lotteries
From Winning to Understanding: A Diagnostic Long-Horizon RTS Benchmark for LLMs
On Minimum Depth and Width of Floating-Point Neural Networks for Representing Floating-Point Functions
Non-Parametric Optimization for Scalable Learning in Stochastic Decision Problems
From Absolute to Relative: Rethinking Reward Shaping in Group-Based Reinforcement Learning
Robust Linear Dueling Bandits with Post-serving Context under Unknown Delays and Adversarial Corruptions
Discounted Beta-Bernoulli Reward Estimation for Sample-Efficient Reinforcement Learning with Verifiable Rewards
Recovering Policy-Induced Errors: Benchmarking and Trajectory Synthesis for Robust GUI Agents
Theoretical Perspectives on Data Quality and Synergistic Effects in Pre- and Post-Training Reasoning Models
LAST: Bridging Vision-Language and Action Manifolds via Gromov-Wasserstein Alignment
You Can Learn Tokenization End-to-End with Reinforcement Learning
Conditional Quantile Adjusted Conformal Prediction for Time Series
AnalogVerifier: A Neuro-Symbolic Framework for Analog Circuit Verification
Winformer: Transcending Pairwise Similarity for Time-series Generation
The Invisible Lottery: How Subtle Cues Steer Algorithm Choice in LLM Code Generation
Scaling Continual Learning with Bi-Level Routing Mixture-of-Experts
Position: Neural Approximation Is Rarely Justified for Hard Combinatorial Problems
Talk, Judge, Cooperate: Gossip-Driven Indirect Reciprocity in Self-Interested LLM Agents
Evolving Interdependent Operators with Large Language Models for Multi-Objective Combinatorial Optimization
Visual Persuasion: What Influences Decisions of Vision-Language Models?
Matroid Algorithms Under Size-Sensitive Independence Oracles
Opt-Verifier: Unleashing the Power of LLMs for Optimization Modeling via Dual-Side Verification
Position: Behavioral Systems Require Behavioral Tests
Local-Minima-Preserving Polynomial Relaxation of Ising Problems
Opt-Miner: Empowering Information-Seeking Agent with Tree-Guided Data Synthesis for Optimization Modeling
Making Models Unmergeable via Scaling-Sensitive Loss Landscape
Structured Progressive Knowledge Activation for LLM-Driven Neural Architecture Search
Dynamic Stratified Contrastive Learning with Upstream Augmentation for MILP Branching
ModernVBERT: Towards Smaller Visual Document Retrievers
Problem Distributions as Tasks: Repurposing Meta Learning for Generative Combinatorial Optimization towards Multi-task Pretrain and Adaptation
Jailbreak Foundry: From Papers to Runnable Attacks for Reproducible Benchmarking
Graph-R1: Towards Agentic GraphRAG Framework via End-to-end Reinforcement Learning
From Volume to Value: Preference-Aligned Memory Construction for On-Device RAG
Simple Algorithms for Bad Triangle Transversals with Applications to Correlation Clustering
Variational Routing: A Scalable Bayesian Framework for Calibrated Mixture-of-Experts Transformers
NAVIGATE: Evaluating Visual-Guided Search Decision-Making on the Open Web
PathWise: Planning through World Model for Automated Heuristic Design via Self-Evolving LLMs
Med-SegLens: Latent-Level Model Diffing for Interpretable Medical Image Segmentation
LIF Recurrent Memory Enables Long-Horizon Spiking Computation
Finding the Correct Visual Evidence Without Forgetting: Mitigating Hallucination in LVLMs via Inter-Layer Visual Attention Discrepancy
Spatial Priors via Space Filling Curves for Small and Limited Data Vision Transformers
PoMtVRS: Preference-Optimized Multi-Task Vehicle Routing Solver with Preference Gating
Unsupervised Diffusion for Combinatorial Optimization via Adjoint Matching
Prompt Estimation from Prototypes for Federated Prompt Tuning of Vision Transformers
D$^2$O: A Dual Debiasing Operator for Training-Free Test-Time Adaptation of Vision–Language Models
Controlled LLM Training on Spectral Sphere
Gradient Descent as a Perceptron Algorithm: Understanding Dynamics and Implicit Acceleration
Near-Universal Multiplicative Updates for Nonnegative Einsum Factorization
Position: Profiling Game Worlds by Transition Complexity
ECCO: Evidence-Driven Causal Reasoning for Compiler Optimization
Does Reinforcement Fine-Tuning Improve Generalization of LLM Agents? An Empirical Study
PISCES: Annotation-free Text-to-Video Post-Training via Optimal Transport-Aligned Rewards
GradientStabilizer: Fix the Norm, Not the Gradient
Radial Scaling Voxelization for Accurate Small Object 3D Detection
Solving Stochastic Variational Inequalities without the Bounded Variance Assumption
A General Neural Backbone for Mixed-Integer Linear Optimization via Dual Attention
Exploiting weight-space symmetries for approximating curvature
Probing RLVR Training Instability through the Lens of Objective-Level Hacking
Supervised Guidance Training for Infinite-Dimensional Diffusion Models
Dimension-Free Multimodal Sampling via Preconditioned Annealed Langevin Dynamics
Selective Concept Bottleneck Models Without Predefined Concepts
Domain Restriction via SAE Multi-Layer Transitions
Provable Training Data Identification for Large Language Models
SVD as a Fast Interpretability Method for Transformers
Beyond External Monitors: Enhancing Transparency of Large Language Models for Easier Monitoring
Certified Circuits: Stability Guarantees for Mechanistic Circuits
On The Variability Of Concept Activation Vectors
How does Bayesian Sampling help Membership Inference Attacks?
A Distributional View for Visual Mechanistic Interpretability: KL-Minimal Soft-Constraint Principle
C$^{2}$R: Cross-sample Consistency Regularization Mitigates Feature Splitting and Absorption in Sparse Autoencoders
DREAM-R: Multimodal Speculative Reasoning with RL-Based Refined Drafting, Precise Verification, and Fully Parallel Execution
Block-wise Codeword Embedding for Reliable Multi-bit Text Watermarking
AMDP: Asynchronous Multi-Directional Pipeline Parallelism for Large-Scale Models Training
PathwayLLM: Explainable Clinical Trajectory Modeling with Structured Pathways for Sepsis Prediction
In-Context Learning as Rate–Distortion Optimization
Finding Most Influential Sets
Sparse but Wrong: Incorrect L0 Leads to Incorrect Features in Sparse Autoencoders
Early Decisions Matter: Proximity Bias and Initial Trajectory Shaping in Non-Autoregressive Diffusion Language Models
Hidden in Plain Tokens: Simply Robust, Gradient-Free Watermark for Synthetic Audio
Certificate-Guided Pruning for Stochastic Lipschitz Optimization
Learning a Generative Meta-Model of LLM Activations
Betting on Equilibrium: Monitoring Strategic Behavior in Multi-Agent Systems
Group-wise Data Ordering: Enhancing Instruction Tuning of Large Language Models via Embedding Proximity
Cutting LLM Evaluation Costs with SySRs: A Bandit Algorithm that Provably Exploits Model Similarity
Probing Cross-modal Information Hubs in Audio-Visual LLMs
PhotoAgent: Exploratory Visual Aesthetic Planning with Large Vision Models
RAIGen: Rare Attribute Identification in Text-to-Image Generative Models
The Assistant Axis: Situating and Stabilizing the Default Persona of Language Models
A Regret Minimization Framework on Preference Learning in Large Language Models
Interpreting and Enhancing Emotional Circuits in Large Vision-Language Models via Cross-Modal Information Flow
Position: Anthropomorphic Misalignment Research Needs Stronger Evidence
Q-Flow: Stable and Expressive Reinforcement Learning with Flow-based Policy
JANUS-LORA: A Balanced Low-Rank Adaptation for Continual Learning
Transitivity Meets Cyclicity: Explicit Preference Decomposition for Dynamic Large Language Model Alignment
Multi-Adapter Representation Interventions via Energy Calibration
BLOCK-EM: Preventing Emergent Misalignment via Latent Blocking
Width Independent Bounds for the Local Lipschitz Constant of Deep Neural Networks at Random Initialization and after Lazy Training
Expectation Alignment of Language Models for Real-World User Expectations
Simultaneous Multi-objective Alignment Across Verifiable and Non-verifiable Rewards
Conflict-Aware Adaptive Alignment for LLM Hallucination Mitigation
FullStack-Agent: Enhancing Agentic Full-Stack Web Coding via Development-Oriented Testing and Repository Back-Translation
The Obfuscation Atlas: Mapping Where Honesty Emerges in RLVR with Deception Probes
Angel or Demon: Investigating the Plasticity Interventions' Impact on Backdoor Threats in Deep Reinforcement Learning
Latent Space Robust Optimization of Neural Processes with Aligned Stratified Order-Statistic Loss Reduction
ST-Veto: Spatio-Temporal Token Veto for Diffusion MLLMs via Taylor Prediction and Visual Grounding
BVS: Bayesian Visual Search with Multimodal Large Language Model for Fine-grained Perception
Contextual Rollout Bandits for Reinforcement Learning with Verifiable Rewards
LMM4-IC4K: A Large Multimodal Model Powered Integrated Circuit Footprint Geometry Understanding
Position: Academic Conferences are Potentially Facing Denominator Gaming Caused by Fully Automated Scientific Agents
Position: Safe AI Should be Resistant and Resilient in an Evolving World
MINIF2F-DAFNY: LLM-Guided Mathematical Theorem Proving via Auto-Active Verification
Position: Child Safety Necessitates New Approaches to AI Safety
Position: Safe Models Do Not Guarantee Safe Societies: The Case for Sociopolitical Risk
Can Adaptive Gradient Methods Converge under Heavy-Tailed Noise? A Case Study of AdaGrad
Hard-Constrained Graph Generation with Discrete-Projection Diffusion
Fleet: Few-Shots Lead Effective AIGI Detection
Reasoning Models Struggle to Control their Chains of Thought
REALISTA: Realistic Latent Adversarial Attacks that Elicit LLM Hallucinations
Securing Multimodal AI through Internal Information Decomposition
OpenDeception: Learning Deception and Trust in Human–AI Interaction via Multi-Agent Simulation
Metis: Learning to Jailbreak LLMs via Self-Evolving Metacognitive Policy Optimization
Faithful Mobile GUI Agents with Guided Advantage Estimator
Cure-SFT: Diagnostic-Guided Data Curation for Instruction Tuning
Just Ask: Curious Code Agents Reveal System Prompts in Frontier LLMs
STARE: Step-wise Temporal Alignment and Red-teaming Engine for Multi-modal Toxicity Attack
Self-supervised Hierarchical Visual Reasoning with World Model
Debate with Images: Detecting Deceptive Behaviors in Multimodal Large Language Models
Temporal Preference Optimization for Unsupervised Retrieval
How does information access affect LLM monitors' ability to detect sabotage?
Riemannian MeanFlow
Bayesian Tensor Decomposition with Diffusion Model Prior
Riemannian MeanFlow for One-Step Generation on Manifolds
Meerkat-VL: Implicit Risk Safety Alignment in Multimodal LLMs via Perceptual Reasoning and Self-Verification
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
Calibrating Uncertainty for Zero-Shot Adversarial CLIP
Agent World Model: Infinity Synthetic Environments for Agentic Reinforcement Learning
Test-Time Anchoring for Discrete Diffusion Posterior Sampling
Covariance estimation using Markov chain Monte Carlo
PhysHanDI: Physics-Based Reconstruction of Hand-Deformable Object Interactions
Learning Efficient Guardrails for Compliance
UniPercept: Towards Unified Perceptual-Level Image Understanding across Aesthetics, Quality, Structure, and Texture
The Optimal Token Baseline: Variance Reduction for Long-Horizon LLM-RL
Reflector: Internalizing Step-wise Reflection against Indirect Jailbreaks
Diffusion Flow Matching: Dimension-Improved KL Bounds and Wasserstein Guarantees
Modelling Attention with Aitchison Geometry: Token Distinguishability and Temperature Scaling
SetPO: Set-Level Policy Optimization for Diversity-Preserving LLM Reasoning
TokenSwap: Backdoor Attack on the Compositional Understanding of Large Vision-Language Models
From Per-Image Low-Rank to Encoding Mismatch: Rethinking Feature Distillation in Vision Transformers
OmniMoE: An Efficient MoE by Orchestrating Atomic Experts at Scale
Clover: Accurate LLM Pre-Training in NVFP4 by Improved Unbiased Gradient Estimation
OptProver: Bridging Olympiad and Optimization through Continual Training in Formal Theorem Proving
Diffusion Models Preferentially Memorize Prototypical Examples or: Why Does My Diffusion Model Love Slop?
What You Think is What You See: Driving Exploration in VLM Agents via Visual-Linguistic Curiosity
BEAT: Tokenizing and Generating Symbolic Music by Uniform Temporal Steps
ImpText: A Benchmark and Tool-Augmented Framework for Implicit Text Reasoning
DecFus: Decentralized Layer-wise Fusion with Dynamic Exploration and Exploitation
A Two-Layer Framework for Joint Online Configuration Selection and Admission Control
PRISM: Distribution-free Adaptive Computation of Matrix Functions for Accelerating Neural Network Training
HVR-Met: A Hypothesis-Verification-Replaning Agentic System for Extreme Weather Diagnosis
Unveiling the Potential of Quantization with MXFP4: Strategies for Quantization Error Reduction
IO-Adam: Rethinking Memory-Efficient Adaptive Optimizers from Gradient Computation
Disease-Centric Vision-Language Pretraining with Hybrid Visual Encoding for 3D Computed Tomography
MAPS: Memory-Aware Predictive Scheduling Framework for Large Language Models Serving
Seeing is Understanding: Unlocking Causal Attention into Modality-Mutual Attention for Multimodal LLMs
Geometric Entropy and Retrieval Phase Transitions in Continuous Thermal Dense Associative Memory
DecoderTCR: Compositional Pretraining and Entropy-Guided Decoding for TCR-pMHC Interactions
SALE : Low-bit Estimation for Efficient Sparse Attention in Long-context LLM Prefilling
WISE: World Knowledge-Informed Semantic Evaluation for Text-to-Image Generation
Dynamic Regret via Discounted-to-Dynamic Reduction with Applications to Curved Losses and Adam Optimizer
Decomposing Query-Key Feature Interactions Using Contrastive Covariances
Optimal Anytime Algorithms for Online Convex Optimization with Adversarial Constraints
When AI Benchmarks Plateau: A Systematic Study of Benchmark Saturation
The Interplay Between Interpolation and Aggregation in Regression: Optimal Sample Complexity
VENOMREC: Cross-Modal Interactive Poisoning for Targeted Promotion in Multimodal LLM Recommender Systems
Reinforcement Learning for Reachability: Guaranteeing Asymptotic Optimality
HilbertA: Hilbert-Curve–Aligned Sparse Attention for 2D Structured Data
MixtureVitae: Open Web-Scale Pretraining Dataset With High Quality Instruction and Reasoning Data Built from Permissive-First Text Sources
A Linear Expectation Constraint for Selective Prediction and Routing with False-Discovery Control
DiLA: Disentangled Latent Action World Models
MoST: Mixing Speech and Text with Modality-Aware Mixture of Experts
R$^3$L: Reasoning 3D Layouts from Relative Spatial Relations
Conditional Equivalence of DPO and RLHF: Assumptions, Failure Modes, and Provable Alignment
Dream-MPC: Gradient-Based Model Predictive Control with Latent Imagination
Universal Redundancies in Time Series Foundation Models
Transformed Latent Variable Multi-Output Gaussian Processes
TransNormal: Dense Visual Semantics for Diffusion-based Transparent Object Normal Estimation
ScDiVa: Masked Discrete Diffusion for Joint Modeling of Single-Cell Identity and Expression
Preference Goal Tuning: Post-Training as Latent Control for Frozen Policies
Spiked-CFR: Causal Representation Learning from LLMs via Wasserstein Projection Pursuit
Preference-Calibrated Optimization with Score-Level Distribution Alignment for Text-to-Image Diffusion Model Unlearning
Rethinking generative image pretraining: How far are we from scaling up next-pixel prediction?
MuCO: Generative Peptide Cyclization Empowered by Multi-stage Conformation Optimization
EDCO: Dynamic Curriculum Orchestration for Domain-specific Large Language Model Fine-tuning
The Efficiency Gap in Byte Modeling
From Noise to Intent: Anchoring Generative VLA Policies with Residual Bridges
$\phi$-Balancing for Mixture-of-Experts Training
Giving Sensors a Voice: Multimodal JEPA for Semantic Time-Series Embeddings
Efficient Hallucination Detection for LLMs Using Uncertainty-Aware Attention Heads
Balancing Understanding and Generation in Discrete Diffusion Models
Hierarchical Procedural Meta-Reasoning for Generalizable Multimodal Agents
One-Step Residual Shifting Diffusion for Image Super-Resolution via Distillation
FoundObj: Self-supervised Foundation Models as Rewards for Label-free 3D Object Segmentation
ProtoVAR: Efficient Dataset Distillation via Prototype-Guided Visual Autoregressive Modeling
Rex: A Family of Reversible Exponential (Stochastic) Runge-Kutta Solvers
Position: Verifiable Data Minimization is a Prerequisite for Responsible, Privacy-Preserving Industrial Vision
Causal Forcing: Autoregressive Diffusion Distillation Done Right for High-Quality Real-Time Video Generation
RapTB: Rooted Absorbed Trajectory Balance with Submodular Replay for Stable Autoregressive GFlowNet Training
Motion-Aware Caching for Efficient Autoregressive Video Generation
Light Forcing: Accelerating Autoregressive Video Diffusion via Sparse Attention
LogicSAGE: Neuro-Symbolic Reasoning with Socratic-Guided Enhancement
DynaMem: Consistent Long Video Generation via Hierarchical Memory and Motion Priors
SONAR: Spectral‑Contrastive Audio Residuals for Generalizable Deepfake Detection
dLLM-Cache: Accelerating Diffusion Large Language Models with Adaptive Caching
Emergent Communication Under Misinformation
EMBGUARD: Constructing Hazard-Aware Guardrails for Safe Planning in Embodied Agents
STRIDE: Post-Training LLMs to Reason and Refine Bio-Sequences via Edit Trajectories
A Solver-Free Training Method for Predict-then-Optimize
Deep Forcing: Training-Free Long Video Generation with Deep Sink and Participative Compression
From Interactions to Principles: Experience-Driven Self-Distillation for Evolving LLM Agents
Boundary Embedding Shaping with Adaptive Contrastive Learning for Graph Structural Disentanglement
RACER: Risk-Aware Calibrated Efficient Routing for Large Language Models
CoF-T2I: Video Models as Pure Visual Reasoners for Text-to-Image Generation
TransLight: Image-Guided Customized Lighting Control with Generative Decoupling
GFFMERGE: Efficient Merging of Graph Neural Force Fields and Beyond
Domain Adaptive Object Detection via Dynamic Causal Refinement
AgentTailor: A Semantic-Aware LLM-Based Multi-Agent System with Actor-Critic Structure
MoFO: Momentum-Filtered Optimizer for Mitigating Forgetting in LLM Fine-Tuning
Towards Efficient Large Language Reasoning Models via Extreme-Ratio Chain-of-Thought Compression
Position: LLM Agents Are the Antidote to Walled Gardens
From Player to Master: Enhancing Test-Time Learning of LLM Agents via Reinforcement Learning over Memory
Inner-layer Token Self-Modulation as Another Scaling Axis for LLMs
VimRAG: Navigating Massive Visual Context in Retrieval-Augmented Generation via Multimodal Memory Graph
Gradients with Respect to Semantics Preserving Embeddings Tell the Uncertainty of Large Language Model
Towards Diverse Scientific Hypothesis Search with Large Language Models
Causal Disentangled Anchor Learning for Scalable Fair Multi-view Clustering
Reward Auditor: Inference on Reward Modeling Suitability in Real-World Perturbed Scenarios
Unified Episodic and Semantic Memory via Modulating Transformer FeedForward Layers
Hedging on the frontier: Learning new tasks with few samples
Variational Speculative Decoding: Rethinking Draft Training from Token Likelihood to Sequence Acceptance
RGGT: A Generative-Prior-Guided Transformer for Unified Rigid and Non-Rigid Point Cloud Registration
AutoRAS: Learning Robust Agentic Systems with Primitive Representations
NeUQI: Near-Optimal Uniform Quantization Parameter Initialization for Low-Bit LLMs
How to Train Your Advisor: Steering Black-Box LLMs with Advisor Models
Efficient numeracy in language models through single-token number embeddings
Towards Complete Multi-Agent Coordination Policy Learning via Denoising Maximum Entropy Optimization
Capacity-Aware Mixture Law Enables Efficient LLM Data Optimization
SemBind: Binding Diffusion Watermarks to Semantics Against Black-Box Forgery Attacks
Least-Loaded Expert Parallelism: Load Balancing An Imbalanced Mixture-of-Experts
Maximum Likelihood Reinforcement Learning
From Growing to Looping: A Unified View of Iterative Computation in LLMs
Deep Flow Networks
From Intent to Solver Code: Semantic Alignment in Optimization Modeling
Orthogonal Concept Erasure for Diffusion Models
Less Is More: Elevating RAG via Performance-Driven Context Compression
$\texttt{Multi}^2$: Hierarchical Multi-Agent Decision-Making with LLM-Based Agents in Interactive Environments
Low-cost Full Fine-tuning: Learning What to Update for LLMs
Mind the Gap: Structure-Aware Consistency in Preference Learning
Chain-of-Glimpse: Search-Guided Progressive Object-Grounded Reasoning for Video Understanding
Cache Coherent Resampling for Efficient Test Time Scaling in LLM Reasoning via Adaptive Sequential Monte Carlo
GaussTrace: Provenance Analysis of 3D Gaussian Splatting Models with Evidence-based LLM Reasoning
Decomposed On-Policy Distillation for Vision-Language Reasoning: Steering Gradients for Visual Grounding
Approximation Error Upper and Lower Bounds for Hölder Class with Transformers
Small Agent Group is the Future of Digital Health
$R^3$DAO: Reactive Recovery and Reconstruction for Long-horizon Data Agent Orchestration
The Secret Engine Behind RLHF: It's Contarstive Learning All Along
A model of errors in transformers
UniRRM: Unified Reasoning Reward Models Across Languages and Evaluation Paradigms
Smaller Models are Natural Explorers for Policy-Level Diversity in GRPO
Unsupervised Mode Discovery for Fine-tuning Multimodal Generative Policies
Generalizing Multi-Scale Time-Series Modeling with a Single Operator
(De)-regularized Maximum Mean Discrepancy Gradient Flow
Training–Inference Consistent Segmented Execution for Long-Context LLMs
AOEPT: Breaking the Implicit Modality-Reduction Bottleneck in Modality Missing Prompt Tuning
Benchmarking LLM-Assisted Blue Teaming via Standardized Threat Hunting
PlotCraft: Pushing the Limits of LLMs for Complex and Interactive Data Visualization
Chiral Symmetry Breaking in Transformers: A Group-Equivariant Framework for Solving the Reversal Curse via Adjoint Manifold Mappings
Scaling Agentic Verifier for Competitive Coding
TreeCUA: Efficiently Scaling GUI Automation with Tree-Structured Verifiable Evolution
Neural Logistic Bandits
SciAgentGym: Benchmarking Multi-Step Scientific Tool-Use in LLM Agents
DDIM Inversion as a Perturbation Amplifier: Breaking Mimicry Protection via Reconstruction Error Minimization
Geometry-Aware Contrastive Learning for Few-Shot Automatic Modulation Recognition
TruthRL: Incentivizing Truthful LLMs via Reinforcement Learning
Closing the Expression Gap in LLM Instructions via Socratic Questioning
Dependence-Aware Label Aggregation for LLM-as-a-Judge via Ising Models
ThetaEvolve: Test-time Learning on Open Problems
T-Edit: Triple-Branch Diffusion Anchoring for Consistent Editing
Backward Oversmoothing: why is it hard to train deep Graph Neural Networks?
The Velocity Deficit: Initial Energy Injection for Flow Matching
Less is More: Geometric Unlearning for LLMs with Minimal Data Disclosure
Harnessing Uncertainty: Entropy-Modulated Policy Gradients for Long-Horizon LLM Agents
On the "Induction Bias" in Sequence Models
SHINE: A Scalable In-Context Hypernetwork for Mapping Context to LoRA in a Single Pass
FAIR-Calib: Frontier-Aware Instability-Reweighted Calibration for Post-Training Quantization of Diffusion Large Language Models
Training AI Co-Scientists Using Rubric Rewards
Effective MoE-based LLM Compression by Exploiting Heterogeneous Inter-Group Experts Routing Frequency and Information Density
Hybrid Policy Distillation for LLMs
No Global Plan in Sight: Uncover the Myopic Planning Horizon of LLMs
SWE-ABS: Adversarial Benchmark Strengthening Exposes Inflated Success Rates on Test-based Benchmark
ZeroBench: An Impossible Visual Benchmark for Contemporary Large Multimodal Models
AugServe: Adaptive Request Scheduling for Augmented Large Language Model Inference Serving
Efficient Parallel Samplers for Recurrent-Depth Models
Language as a Wave Phenomenon: Semantic Phase Locking and Interference in Neural Networks
Fine-Tuning Without Forgetting In-Context Learning: A Theoretical Analysis of Linear Attention Models
Dr. Kernel: Reinforcement Learning Done Right for Triton Kernel Generations
Linear Bandits beyond Inner Product Spaces, the case of Bandit Optimal Transport
On Multi-Step Theorem Prediction via Non-Parametric Structural Priors
PartCo: Part-Level Correspondence Priors Enhance Category Discovery
On the Plasticity and Stability for Post-Training Large Language Models
CAMEL: Confidence-Gated Reflection for Reward Modeling
NExT-Guard: Training-Free Streaming Safeguard without Token-Level Labels
TEFormer: Structured Bidirectional Temporal Enhancement Modeling in Spiking Transformers
Contrastive Weak-to-Strong Generalization
SafeSci: Safety Evaluation of Large Language Models in Science Domains and Beyond
The Shape of Addition: Geometric Structures of Arithmetic in Large Language Models
Memory as a Markov Matrix: Sample Efficient Knowledge Expansion via Token-to-Dictionary Mapping
ScaLoRA: Optimally Scaled Low-Rank Adaptation for Efficient High-Rank Fine-Tuning
Enhancing Multi-Modal LLMs Reasoning via Difficulty-Aware Group Normalization
NaRA: Noise-Aware LoRA for Parameter-Efficient Fine-Tuning of Diffusion LLMs
Improved Stochastic Optimization of LogSumExp
Reasoning over Boundaries: Enhancing Specification Alignment via Test-time Deliberation
Revisiting Robustness for LLM Safety Alignment via Selective Geometry Control
Don't Forget Why You Started: Tackling Dual Forgetting in Vision-Language Continual Learning
R-Diverse: Mitigating Diversity Illusion in Self-Play LLM Training
Spectral Evolution Search: Efficient Inference-Time Scaling for Reward-Aligned Image Generation
Learning to Move Before Learning to Do: Task-Agnostic pretraining for VLAs
TsLLM: Augmenting LLMs for General Time Series Understanding and Prediction
From Diagrams to Code: Multilingual Programming with Visual Design
InvGNN: Learning Invertible Node Representations on Graphs
ERAlign: Energy-based Representation Alignment of GNNs and LLMs on Text-attributed Graphs
Generation Enhances Understanding in Unified Multimodal Models via Multi-Representation Generation
Depth-Breadth Synergy in RLVR: Unlocking LLM Reasoning Gains with Adaptive Exploration
ParisKV: Fast and Drift-Robust KV-Cache Retrieval for Long-Context LLMs
SpecPrune-VLA: Accelerating Vision-Language-Action Models via Action-Aware Self-Speculative Pruning
Efficient, Validation-Free Intrinsic Quality Estimation for Large-Scale Face Recognition Datasets
Towards Understanding Modality Interaction in Multimodal Language Models via Partial Information Decomposition
AVI-Bench: Toward Human-like Audio-Visual Intelligence of Omni-MLLMs
Variational Adapter for Cross-modal Similarity Representation
FG-CLIP 2: A Bilingual Fine-grained Vision-Language Alignment Model
MalTree: Tracing Malware Evolution using Embeddings at Scale
Not All Invariants Are Equal: Curating Training Data to Accelerate Program Verification with SLMs
Multimodal Function Vectors for Spatial Relations
Video2GUI: Synthesizing Large-Scale Interaction Trajectories for Generalized GUI Agent Pretraining
Denoising without Diffusion: Fixed-Noise Denoiser Anomaly Detection in Tabular Data
Your Latent Reasoning is Secretly Policy Improvement Operator
This State Looks Like That: Self-Interpretable Reinforcement Learning Agents using Prototype Soft Actor-Critic
PS-PPO : Prefix-Sampling PPO for Critic-Free RLHF
TabularBERT: Binning-Based Self-Supervised Learning for Tabular Representation
Inference Time Concept Removal Guidance for Text-to-Image Diffusion Models
MapUQ: Map with Uncertainty Quantification for Robust BEV Vectorized Construction
CACR: Reinforcing Temporal Answer Grounding in Instructional Video via Candidate-Aware Causal Reasoning
Grounding Functional Similarity by Invariance-Aware Model Stitching
JADE: Bridging the Strategic-Operational Gap in Dynamic Agentic RAG
Learning to Refine: Spectral-Decoupled Iterative Refinement Framework for Precipitation Nowcasting
A Geometry-Based View of Mahalanobis OOD Detection
LoPhyDA: Low-Rank Tensor and Physics Gradient Guided Diffusion for Atmospheric Data Assimilation
Zeus: Towards Tuning-Free Foundation Model for Time Series Analysis
Correct looks better: Pairwise comparisons reveal accuracy rankings
Evaluating LLM Uncertainty in Long-Form Generation Using Deterministic Ground Truth
Byte Pair Encoding for Efficient Time Series Forecasting
Efficient Learned Image Compression without Entropy Coding
OmniVideo-R1: Reinforcing Audio-visual Reasoning with Query Intention and Modality Attention
IMPACT: Influence Modeling for Open-Set Time Series Anomaly Detection
One Batch Is Enough: A Unified Dataset Condensation Framework for General Time Series Analysis
HypCL: Adapting CLIP in Hyperbolic Space for Continual Learning
Early Directional Convergence in Deep Homogeneous Neural Networks for Small Initializations
THETA: Threshold-Based Exclusive Batching for Memory-Bandwidth-Constrained LLM Inference
Curating the Future: A Scalable Recipe for Training Open-Ended Forecasters
Feature Resemblance: Towards a Theoretical Understanding of Analogical Reasoning in Transformers
Deep Coupling Learning for Solving PDEs
[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
Learning a Zeroth-Order Optimizer for Fine-Tuning LLMs
Geometry-Preserving Unsupervised Alignment for Heterogeneous Foundation Models
The Entropic Signature of Class Speciation in Diffusion Models
Unraveling Syntax: Language Modeling and the Substructure of Grammars
Reward Shaping Control Variates for Off-Policy Evaluation Under Sparse Rewards
Understanding the Performance Gap in Preference Learning: A Dichotomy of RLHF and DPO
Dependency-Aware Parallel Decoding via Attention for Diffusion LLMs
Beyond Structural Symmetries: Linear Mode Connectivity via Neuron Identifiability
Step-resolved data attribution for looped transformers
Position: LLM for Physics Research Requires Domain-Specialized Training and Tooling
$E^2$PO: Embedding-perturbed Exploration Preference Optimization for Flow Models
Two-Parameter Flows for Learning Population Dynamics of Physical Systems
Enhancing Train-Free Infinite-Frame Generation for Consistent Long Videos
Efficient Multi-round LLM Inference over Disaggregated Serving
Old Habits Die Hard: How Conversational History Geometrically Traps LLMs
Autoregressive Boltzmann Generators
Beyond Drift: Stabilizing Subjective LLM Evaluation with Information-Theoretic Rubrics
Position: Interpretability Can Be Actionable
Learning Permutation-invariant Macroscopic Dynamics
Adaptive Bandit Algorithms for Contextual Matching Markets
TWLA: Breaking the Barrier to W1.58A4 Post-Training Quantization for LLMs
Do-Prompt: Causal Interventions Meet Variational Prompt Bottlenecks
RESIDUAL-GUIDED MULTI-RESOLUTION REFINEMENT OF FOUNDATION MODELS - A CASE STUDY IN DROUGHT FORECASTING
IAPO: Information-Aware Policy Optimization for Token-Efficient Reasoning
CocoRNA: Collective RNA Design with Cooperative Multi-agent Reinforcement Learning
Query Circuits: Explaining How Language Models Answer User Prompts
Beyond Continuity: Simulation-free Reconstruction of Discrete Branching Dynamics from Single-cell Snapshots
Invariant Representation Learning for Source-Free Time Series Forecasting with LLM-Centric Proxy Denoising
LABO: LLM-Accelerated Bayesian Optimization through Broad Exploration and Selective Experimentation
Position: Token Taxes Can Mitigate AI's Economic Risks
MineDraft: A Framework for Batch Parallel Speculative Decoding
Towards Sub-second Biological Foundation Model Infrastructure: A Quantized Consistency Diffusion Framework for Molecular Docking
AutoControl Arena: Synthesizing Executable Test Environments for Frontier AI Risk Evaluation
Provably Protecting Fine-Tuned LLMs from Training Data Extraction
PLSemanticsBench: A Formal Semantics Reasoning Benchmark for Code
Position: Don't Just "Fix it in Post'': A Science of AI Must Study Learning Dynamics
ClimateAR: Multi-Scale Autoregressive Generative Modeling for Seasonal-to-Interannual Climate Forecasting
Nonparametric LLM Evaluation from Preference Data
TimeSpot: Benchmarking Geo-Temporal Understanding in Vision–Language Models in Real-World Settings
Geometry-Aware Neural Optimizer for Shape Optimization and Inversion
A Geometric Lens on Physics-Aligned Data Compression
The Choice of Normalization Influences Shrinkage in Regularized Regression
U-Cast: A Surprisingly Simple Frontier Probabilistic AI Weather Forecaster
Training Diffusion Language Models for Black-Box Optimization
A Dirac-Frenkel-Onsager principle: Instantaneous residual minimization with gauge momentum for nonlinear parametrizations of PDE solutions
Position: There are futures that benchmark-driven AI cannot see
StormInsight: Hierarchical Environmental Forcing and Vertical Coupling for Weather System Evolution
When to Think, When to Speak: Learning Disclosure Policies for Large Language Model Reasoning
Coupled Trigger Optimization and Vulnerable Parameter Alignment for Persistent Backdoor Attacks on Federated Learning
Training-free Composition of Pre-trained GFlowNets for Multi-Objective Generation
EngiAgent: Fully Connected Coordination of LLM Agents for Solving Open-ended Engineering Problems with Feasible Solutions
From Feasible to Practical: Pareto-Optimal Synthesis Planning
Position: AI Lock-In Is in Progress, and We Must Be Prepared
Elign: Equivariant Diffusion Model Alignment from Foundational Machine Learned Force Fields
Position: Beyond Prediction: Toward Verifiable Physiological Waveform Reasoning with Foundation Models and Agentic LLMs
DyPE: Dynamic Position Extrapolation for Ultra High Resolution Diffusion
Approximate Equivariance via Projection-Based Regularisation
Semantic Integrity Matters: Benchmarking and Preserving High-Density Reasoning in KV Cache Compression
UMEM: Unified Memory Extraction and Management Framework for Generalizable Memory
SeisMark: A Large-Scale Open Benchmark for Robust 3D Seismic Fault Detection
Optimal Decision-Making Based on Prediction Sets
Hyperparameter Transfer Laws for Non-Recurrent Multi-Path Neural Networks
Designing a Conditional Prior Distribution for Flow-Based Generative Models
PLaID++: A Preference Aligned Language Model for Targeted Inorganic Materials Design
MAMBO-G: Magnitude-Aware Mitigation for Boosted Guidance
SimulCost: A Cost-Aware Benchmark and Toolkit for Automating Physics Simulations with LLMs
Sparse and Faithful Local Explanations with Piecewise Linear Surrogates
An Information-Theoretic Criterion for Efficient Data Synthesis
Bridging Spherical Black-Box Optimizers
Proximal Splitting Methods for Hybrid Differentiable Models
Asymmetric Contrastive Objectives for Efficient Phenotypic Screening
Ambient Dataloops: Generative Models for Dataset Refinement
WFR-MFM: One-Step Inference for Dynamic Unbalanced OT
Lightning Unified Video Editing via In-Context Sparse Attention
Federated Data and Feature Selection by Generalized CUR Decomposition
Don't Drop Dropout: Optimizing Layer Sparsity for Efficient LLM Training and Inference
SpikeVLA: Vision-Language-Action Models with Spiking Neural Networks
Task-Aware Structured Memory for Dynamic Multi-modal In-Context Learning
$\sigma$: Sigmoid Modulation for Ultra High Resolution Diffusion
DiffStyle3D: Consistent 3D Gaussian Stylization via Attention Optimization
LearniBridge: Learnable Calibration of Feature Caching for Diffusion Models Acceleration
APE-Bench: Evaluating Automated Proof Engineering for Formal Math Libraries
One Model to Translate Them All: Universal Any-to-Any Translation for Heterogeneous Collaborative Perception
PromptPilot: Game-Theoretic Multi-Agent Prompt Optimization for Segment Anything
Twins: Learn to Predict Unified Representations with Focal Loss
Pluralistic Leaderboards
Adaptive Token Refinement in Long-Tailed Large Vision-Language Models Fine-Tuning
IEC: When Information-Driven Exploration Meets Spectral Consensus via Primal–Dual Reward Regularization in Decentralized Multi-Agent RL
Temporal-Emerged Prompting for Segment Anything in Multiframe Infrared Small Target Detection
Numina-Lean-Agent: An Open and General Agentic Reasoning System for Formal Mathematics
Task-Driven Subspace Decomposition for Knowledge Sharing and Isolation in LoRA-based Continual Learning
Breaking Manifold Continuity: Vector Quantized Modeling for Real-Centric Deepfake Detection
An Odd Estimator for Shapley Values
SWE-Perf: Can Language Models Optimize Code Performance on Real-World Repositories?
Let Language Constrain Geometry: Vision–Language Models as Semantic and Spatial Critics for 3D Generation
DREAM: A Unified Framework for Drift-Corrected Federated Multi-Objective Learning
Where Detectors Fail: Probing Generative Space for Generalizable AI-Generated Image Detection
EmWorld: Emotion World Model with Latent State Evolution for Scenario-Incremental Dynamic Facial Expression Recognition
Reverse Flow Matching: A Unified Framework for Online Reinforcement Learning with Diffusion and Flow Policies
Interpretable Neural ODEs for Gene Regulatory Network Discovery under Perturbations
ThunderAgent: A Fast, Simple, and Program-Aware Agentic Inference System
Mitigating Surgical Data Imbalance with Dual-Prediction Video Diffusion Model
Position: Self-Play Only Evolves When Self-Synthetic Pipeline Ensures Learnable Information Gain
TGV-KV: Text-Grounded KV Eviction for Vision-Language Models
Hunt Instead of Wait: Evaluating Deep Data Research on Large Language Models
Learning Locally, Revising Globally: Global Reviser for Federated Learning with Noisy Labels
MEAL: A Benchmark for Continual Multi-Agent Reinforcement Learning
SMD: Multi-view Safety-Critical Driving Video Generation in the Real-world Domain
SplAttN: Bridging 2D and 3D with Gaussian Soft Splatting and Attention for Point Cloud Completion
Artificial Hippocampus Networks for Efficient Long-Context Modeling
Ideal Attribution and Faithful Watermarks for Language Models
PACE: Post-Causal Entropy Modeling for Learned LiDAR Point Cloud Compression
Reinforcement Learning for Tool-Calling Agents in Fast Healthcare Interoperability Resources (FHIR)
Position: Text Embeddings Should Capture Implicit Semantics, Not Just Surface Meaning
DASH: Faster Shampoo via Batched Block Preconditioning and Efficient Inverse-Root Solvers
Position: Towards Responsible Evaluation for Text-to-Speech
LoRDO: Distributed Low-Rank Optimization with Infrequent Communication
TOM-SWE: User Mental Modeling For Software Engineering Agents
Sample Margin-Aware Recalibration of Temperature Scaling
The Perception–Physics Paradox: Probing Scientific Alignment with TC-Atlas
Towards Universal Gene Regulatory Network Inference: Unlocking Generalizable Regulatory Knowledge in Single-cell Foundation Models
Topological Active Inference for Task Disambiguation
Reverse-Engineering Model Editing on Language Models
Mind-Omni: A Unified Multi-Task Framework for Brain-Vision-Language Modeling via Discrete Diffusion
LatentChem: From Textual CoT to Latent Thinking in Chemical Reasoning
CaP-X: A Framework for Benchmarking and Improving Coding Agents for Robot Manipulation
DECO: Decoupled Multimodal Diffusion Transformer for Bimanual Dexterous Manipulation with a Plugin Tactile Adapter
ReLAM: Learning Anticipation Model for Rewarding Visual Robotic Manipulation
What Does Thompson Sampling Optimize?
Latent Diffusion Controller: Framework, Algorithms and Parameterization
Improving Explicit Dynamic Gaussian Splatting Optimization via Update Mixture
WinDeskGround: A Benchmark for Robust GUI Grounding in Complex Multi-Window Desktop Environments
Simultaneous Speech-to-Speech Translation Without Aligned Data
Attention Implements the Fisher Geometry of Exponential Families
MADE: Benchmark Environments for Closed-Loop Materials Discovery
LIMMT: Less is More for Motion Tracking
Scene Graph Thinking: Reinforcing Structured Visual Reasoning for Multimodal Large Language Models
RDT2: Exploring the Scaling Limit of UMI Data Towards Zero-Shot Cross-Embodiment Generalization
Modular Pretraining Enables Access Control
Hyperbolic neural population geometry benefits computation
Many-Shot CoT-ICL: Making In-Context Learning Truly Learn
Rethinking Evaluation Paradigms in IBP-based Certified Training
SkillNet: Hierarchical Skill Modeling for Compositional Generalization in Vision-Language Action Models
Sparse ActionGen: Accelerating Diffusion Policy with Real-time Pruning
Self-CriTeach: LLM Self-Teaching and Self-Critiquing for Improving Robotic Planning via Automated Domain Generation
Characterizing Vision-Language-Action Models across XPUs: Constraints and Acceleration for On-Robot Deployment
MixQuant: Pushing the Limits of Block Rotations in Post-Training Quantization
The Loss Is Not Enough: Sampling Conditions and Inductive Bias in Contrastive Representation Learning
Motion Attribution for Video Generation
OXE-AugE: A Large-Scale Robot Augmentation of OXE for Scaling Cross-Embodiment Policy Learning
Latent Reasoning VLA: Latent Thinking and Prediction for Vision-Language-Action Models
AdaGC: Enhancing LLM Pretraining Stability via Adaptive Gradient Clipping
TAGRPO: Boosting GRPO on Image-to-Video Generation with Direct Trajectory Alignment
UGround: Towards Unified Visual Grounding with Unrolled Transformers
Self-Prophetic Decoding to Unlock Visual Search in LVLMs
ABCD: All Biases Come Disguised
Embodied Interpretability: Linking Causal Understanding to Generalization in Vision-Language-Action Models
NavOL: Navigation Policy with Online Imitation Learning
NeurVLA: Unleashing Failure-Handling Capability of Vision-Language-Action Models via Neural-Symbolic Reasoning
TurboGS: Accelerating 3D Gaussian Splatting via Error-Guided Sparse Pixel Sampling and Optimization
Resource-Efficient Reinforcement for Reasoning Large Language Models via Dynamic One-Shot Policy Refinement
New Wide-Net-Casting Jailbreak Attacks Risk Large Models
DOT-MoE: Differentiable Optimal Transport for MoEfication
Minimax-Optimal Policy Regret in Partially Observable Markov Games
Dynamics Are Learned, Not Told: Semi-Supervised Discovery of Latent Dynamics Geometries For Zero-Shot Policy Adaptation
Position: Vector Prompt Interfaces Should Be Exposed to Enable Customization of Large Language Models
CorrectionPlanner: Self-Correction Planner with Reinforcement Learning in Autonomous Driving
HVAE: Hyperbolic Variational Autoencoder For Flexible Knowledge Transfer Across Multiple Domains
Revisiting Asymmetries in Black-box Link Stealing against Graph Neural Networks
Turning Adaptation into Assets: Cross-Domain Bridging for Online Vision-Language Navigation
A Benchmark and Framework for Evaluating Next Action Predictions in Spreadsheets
Demystifying Mergeability: Interpretable Properties to Predict Model Merging Success
Contrastive Representation Regularization for Vision-Language-Action Models
Beyond Next-Token Alignment: Distilling Multimodal Large Language Models via Token Interactions
MIMO-LP: A Multi-Input Multi-Output Framework for Subgraph-based Link Prediction
Persistent Semantic Entities in Tool-Augmented LLM Systems
Mean Flow Policy Optimization
Names Don’t Matter: Symbol-Invariant Transformer for Open-Vocabulary Learning
Dynamic Relational Priming Improves Transformer in Multivariate Time Series
Amodal Instance Segmentation with IRAIS Dataset for Sim-to-Real Transfer
Functional Cache Grafting: Robust and Rapid Code-Policy Synthesis for Embodied Agents
Stop Training for the Worst: Progressive Unmasking Accelerates Masked Diffusion Training
Hierarchical Policy Learning via Spectral Decomposition
Scalable and General Whole-Body Control for Cross-Humanoid Locomotion
LaST$_{0}$: Latent Spatio-Temporal Chain-of-Thought for Robotic Vision-Language-Action Model
The Implicit Bias of Depth: From Neural Collapse to Softmax Codes
Decoupling Regularization and Privacy in Differentially Private Ridge Regression and ERM
Exact Functional ANOVA Decomposition for Categorical Inputs
STEP: Warm-Started Visuomotor Policies with Spatiotemporal Consistency Prediction
Seeing Realism from Simulation: Efficient Video Transfer for Vision-Language-Action Data Augmentation
MVP-LAM: Learning Action-Centric Latent Action via Cross-Viewpoint Reconstruction
LARA: Latent Action Representation Alignment for Vision-Language-Action Models
Learning Human-Robot Collaboration via Heterogeneous-Agent Lyapunov Policy Optimization
Towards Optimal Robustness in Learning-Augmented Paging
HiMe: Hierarchical Embodied Memory for Long-Horizon Vision-Language-Action Control
Dissecting Embodied Abilities in Multimodal Language Models through Skill-level Evaluation and Diagnosis
Making Learner Weakness Actionable for Learning from Demonstration with Novice Teachers
Hierarchical Reinforcement Learning for Sparse-Reward Search in Commutative Algebra
Predicting Large Model Test Losses with a Noisy Quadratic System
SafeDec: Constrained Decoding for Safe Autoregressive Generalist Robot Navigation Policies
Position: LLM-Based Social Simulations Require a Boundary
Why ReLU? A Bit-Model Dichotomy for Deep Network Training
Self-Distilled Reasoner: On-Policy Self-Distillation for Large Language Models
HELIX: Hybrid Encoding with Learnable Identity and Cross-dimensional Synthesis for Time Series Imputation
One-Step Graph-Structured Neural Flows for Irregular Multivariate Time Series Classification
Path-conditioned training: a principled way to rescale ReLU neural networks
BioToken and BioFM – Biologically-Informed Tokenization Enables Accurate and Efficient Genomic Foundation Models
Decompose, Structure, and Repair: A Neuro-Symbolic Framework for Autoformalization via Operator Trees
Blending Supervised and Reinforcement Fine-Tuning with Prefix Sampling
StethoLM: Audio Language Model for Cardiopulmonary Analysis Across Clinical Tasks
Hierarchical Retrieval at Scale: Bridging Transparency and Efficiency
Temporal Difference Learning with Compressed Updates: Error-Feedback meets Reinforcement Learning
Offline Multi-agent Continual Cooperation via Skill Partition and Reuse
RA-Det: Towards Universal Detection of AI-Generated Images via Robustness Asymmetry
Monitoring Monitorability
Sparse Topology-Aware Pairwise Scoring for Large-Scale Multi-Agent Reinforcement Learning
Less Is More: Fast and Accurate Reasoning with Cross-Head Unified Sparse Attention
HPS: Hyperspherical Parameter Sharing for Efficient Multi-Agent Reinforcement Learning
Spatial Deconfounder: Interference-Aware Deconfounding for Spatial Causal Inference
CG-MLLM: Captioning and Generating 3D content via Multi-modal Large Language Models
Vulnerable Agent Identification in Large-Scale Multi-Agent Reinforcement Learning
Active Budget Allocation for Efficient Scaling Law Estimation via Surrogate-Guided Pruning
Learning to Bet for Horizon-Aware Anytime-Valid Testing
Offline Multi-Agent Reinforcement Learning via Sequential Score Decomposition
ProtoKV: Streaming Video Understanding under Delayed Evidence with Summary-State Memory
Automata-Conditioned Cooperative Multi-Agent Reinforcement Learning
Role-Level Inductive Bias for Cross-Task Generalization in Multi-Agent Reinforcement Learning
ECA: Efficient Continual Alignment for Open-Ended Image-to-Text Generation.
Confidence and Difficulty-Adaptive Policy Optimization for LLM Reasoning
mSOP-765k: A Benchmark For Multi-Modal Structured Output Predictions
Decentralized and Disentangled Task–Role Representation Learning for Generalizable Offline Multi-Agent Meta Reinforcement Learning
ReasonEdit: Editing Vision--Language Models using Human Reasoning
PADD: Path-Aligned Decompression Distillation for Non-Router Teacher to Guide MoE Student Learning
Multi-marginal temporal Schrödinger Bridge Matching from unpaired data
Equivariant Latent Alignment via Flow Matching under Group Symmetries
Towards Understanding Generalization of Federated Adversarial Learning: Perspective of Algorithmic Stability
Neuro-Symbolic AI for Analytical Solutions of Differential Equations
Near-Minimax Multi-Objective RL under Predictable Adversarial Preferences and Preference-Free Exploration in Linear MDPs
Towards Disentangled Preference Optimization Dynamics
CrispEdit: Low-Curvature Projections for Scalable Non-Destructive LLM Editing
Hierarchical Successor Representation for Robust Transfer
From Flat Facts to Sharp Hallucinations: Detecting Stubborn Errors via Gradient Sensitivity
Towards Achieving Optimal Strong Regret and Constraint Violation via Computational Efficient Model-free RL
LiteVSR: Enabling Cross-Domain Fine-Grained Detail Generation in Light-Weight Transformers for Video Super-Resolution
Reinforcement-aware Knowledge Distillation for LLM Reasoning
Coverage ≠ Exposure: Auditable Control of Same-Support Tail Failures under Multimodal Missingness
VLAW: Iterative Co-Improvement of Vision-Language-Action Policy and World Model
MMKU-Bench: A Multimodal Update Benchmark for Diverse Visual Knowledge
Outrunning LLM Cutoffs: A Live Kernel Crash Resolution Benchmark for All
The Geometry of Representational Failures in Vision Language Models
Temporal Straightening for Latent Planning
Statistically Optimal Scaling for Token Merging in Transformers
Likelihood over Estimation: Robust Quadratic Discriminant Analysis for Heavy-Tailed Distributions with Theory and Evidence
Escaping Mode Collapse in LLM Generation
Learning Rate Annealing Improves Tuning Robustness in Stochastic Optimization
Target-Oriented Pretraining Data Selection via Neuron-Activated Graph
Universal Learning of Nonlinear Dynamics
GradPower: Powering Gradients for Faster Language Model Pre-Training
GRAPE: Let GRPO Supervise Query Rewriting by Ranking for Retrieval
D-ARL: A Distribution-Matched Asynchronous Reinforcement Learning Framework for Language Reasoning
Advantage Collapse in Group Relative Policy Optimization: Diagnosis and Mitigation
Instruction Decomposition and Action Alignment for Vision-Language Navigation
Implicit Safety Alignment from Crowd Preferences
Dimensional Collapse in Transformer Attention Outputs: A Challenge for Sparse Dictionary Learning
Think-Then-Generate: Reasoning-Aware Text-to-Image Diffusion with LLM Encoders
Weak-to-Strong Generalization via Bregman Bias–Variance Decomposition
Posterior Sampling Reinforcement Learning with Gaussian Processes for Continuous Control: Sublinear Regret Bounds for Unbounded State Spaces
Caracal: Causal Architecture via Spectral Mixing
UniCoD: Enhancing Robot Policy via Unified Continuous and Discrete Representation Learning
PRAC: Principal-Random Subspace for LLM Activation Compression and Memory-Efficient Training
Feedback Control for Multi-Objective Graph Self-Supervision
VCG-Bench: Towards A Unified Visual-Centric Benchmark for Structured Generation and Editing
Beyond Logits: Coherent Hallucination Mitigation via Attention Contrastive Decoding
Less Precise Can Be More Reliable: A Systematic Evaluation of Quantization’s Impact on VLMs Beyond Accuracy
Opportunistic Expert Activation: Batch-Aware Expert Routing for Faster Decode Without Retraining
FedQueue: Queue-Aware Federated Learning for Cross-Facility HPC Training
Beyond Scalars: Evaluating and Understanding LLM Reasoning via Geometric Progress and Stability
Natural Language Actor–Critic Is Bilevel: Learning to Reason with Textual Feedback
From Blind Spots to Gains: Diagnostic-Driven Iterative Training for Large Multimodal Models
Sobolev Regularized Score Difference Estimation in Diffusion Models
What Do Agents Learn from Trajectory-SFT: Semantics or Interfaces?
A Two-Tier Perspective on Inference-Time Parallelism in Multi-Agent LLM Systems
STAND: Self-Aware Precondition Induction for Interactive Task Learning
Towards A Generative Protein Evolution Machine with DPLM-Evo
Stabilized Supralinear Networks Learn to Switch Coding Strategies Balancing Cost and Performance
Guided Star-Shaped Masked Diffusion
Optimizing Agentic Reasoning with Retrieval via Synthetic Semantic Information Gain Reward
Distribution Transformers: Fast Approximate Bayesian Inference With On-The-Fly Prior Adaptation
Training-Free Sparse Attention for Fast Video Generation via Offline Layer-Wise Sparsity Profiling and Online Bidirectional Co-Clustering
BizFinBench.v2: Towards Reliable LLMs in Finance via Real-User Data and Offline/Online Bilingual Evaluation
TodoEvolve: Learning to Architect Agent Planning Systems
Clipping Low-Probability Tokens in SFT Yields a Generalizable Initialization for RL
What Really Improves Mathematical Reasoning: Structured Reasoning Signals Beyond Pure Code
MIMOMamba: From Scalar Duality to Matrix-Valued Attention
Reasoning LLM Improves Speaker Recognition in Long-form TV Dramas
Navigating the Energy Landscape of Collaboration: Multi-Agent Communication Graph Generation via Score-Based Diffusion
Risk Awareness Injection: Calibrating Vision-Language Models for Safety without Compromising Utility
From Directions to Regions: Decomposing Activations in Language Models via Local Geometry
Vibe Checker: Aligning Code Evaluation with Human Preference
Partial Fusion of Neural Networks: Efficient Tradeoffs Between Ensembles and Weight Aggregation
VideoLoom: A Video Large Language Model for Joint Spatial-Temporal Understanding
A Computational Framework for Evaluating Human-likeness in LLMs' Open-ended Human Behaviors
Optimal Learning from Label Proportions with General Loss Functions
Contextualized Privacy Defense for LLM Agents
LFQ: Logit-aware Final-block Quantization for Boosting the Generation Quality of Low-Bit Quantized LLMs
Understanding Multimodal Learning: A Loss Landscape Smoothness Perspective
SleepLM: Natural-Language Intelligence for Human Sleep
Learning to Watch: Active Video Anomaly Understanding via Interleaved Policy Optimization
Context-Driven Incremental Compression for Multi-Turn Dialogue Generation
Any-dimensional invariant universality
Domain Transfer Becomes Identifiable via a Single Alignment
Watermarking LLM Agent Trajectories
Scaling Long-Horizon Agent via Context Folding
On the Coordination of Value-Maximizing Bidders
Distributional Alignment Games for Answer-Level Fine-Tuning
A Risk Decomposition Framework for Pre-hoc Fine-tuning Prediction
Fault Tolerant Multi-Agent Learning with Adversarial Budget Constraints
SPARe: Stacked Parallelism with Adaptive Reordering for Fault-Tolerant LLM Pretraining Systems with 100k+ GPUs
Enhancing Cross-subject Emotion Recognition via Heterogeneous Distribution Augmentation and Collaborative Learning
CausalProfiler: Generating Synthetic Benchmarks for Rigorous and Transparent Evaluation of Causal Machine Learning
EqGINO: Equivariant Geometry-Informed Fourier Neural Operators for 3D Partial Differential Equations
In-Context Learning Is Provably Bayesian Inference: A Generalization Theory for Meta-Learning
Think Twice Before You Act: Enhancing Agent Behavioral Safety with Thought Correction
Decision Tree Learning on Product Spaces
Synthesizable Molecular Generation via Soft-constrained GFlowNets with Rich Chemical Priors
Improved Dimension Dependence for Bandit Convex Optimization with Gradient Variations
Theoretical Investigation on Inductive Bias of Isolation Forest
On Learnability and Disambiguation of Multiclass Partial Concept Classes
A General Framework for Fair and Robust Regression
Sharp empirical Bernstein inequalities for the variance of bounded random variables
Scaling by Diversified Experience for Vision-Language-Action Models
Learning Molecular Semantic Invariant Representation with Prototype Constraint
VeriSimpl: Robust Optimization Modeling from Natural Language using Simplification-based Verification
Improving the Robustness-Utility Trade-off in Decentralized Learning over Sparse Networks
PASO: Step Parallel Stochastic Optimization
Joint Learning in the Gaussian Single Index Model
Taming the Loss Landscape of PINNs with Noisy Feynman–Kac Supervision: Operator Preconditioning and Non-Asymptotic Error Bounds
HARD-KV: Head-Adaptive Regularization for Decoding-time KV Compression
Granularity-Aware Adaptive Classifier Expansion via Zero-Shot Learning
Learning Multi-Timescale Abstractions for Hierarchical Combinatorial Planning
Entropy-informed Decoding: Adaptive Information-Driven Branching
DynaTok: Token-Based 4D Reconstruction from Partial Point Clouds
Position: Stop Preaching and Start Practising Data Frugality for Responsible Development of AI
Statistical-Computational Trade-offs for Recursive Adaptive Partitioning Estimators
SparseSSM: Efficient Selective Structured State Space Models Can Be Pruned in One-Shot
SWE-rebench V2: Language-Agnostic SWE Task Collection at Scale
Towards Solving the Gilbert-Pollak Conjecture via Large Language Models
Linguistic Nepotism: Trading-off Quality for Language Preference in Multilingual RAG
Reward Hacking Benchmark: Measuring Exploits in LLM Agents with Tool Use
Beyond Theorem Proving: Formulation, Framework and Benchmark for Formal Problem-Solving
DLEBench: Evaluating Small-scale Object Editing Ability for Instruction-based Image Editing Model
Systematic Failures in Collective Reasoning under Distributed Information in Multi-Agent LLMs
Position: Agentic AI Is a Foreseeable Pathway to AGI
Fast kernel methods: Sobolev, physics-informed, and additive models
How Can I Publish My LLM Benchmark Without Giving the True Answers Away?
Variational Learning of Disentangled Representations
MFCL Audio: An Audio Function Calling Evaluation for Large Language Models
Quantifying Biases in LLM-as-a-Judge Evaluations
AdaEraser: Training-Free Object Removal via Adaptive Attention Suppression
Error Propagation Mechanisms and Compensation Strategies for Quantized Diffusion Models
Equivariant Neural Networks for General Linear Symmetries on Lie Algebras
DRIFT-BENCH: Diagnosing CoopeRative Breakdowns in LLM Agents under Input Faults via Multi-Turn Interaction
Large-Scale Terminal Agentic Trajectory Generation from Dockerized Environments
Continual Learning of Domain-Invariant Representations
Understanding the Gaps in Satisficing Bandits
Capability-Oriented Training Induced Alignment Risk
Laplacian Representations for Decision-Time Planning
Towards Fair Sequential Decision-Making: A Causal Decomposition Approach
A Control-Theoretic View of Mamba on Stability and Robustness
MetaOthello: A Controlled Study of Multiple World Models in Transformers
Causal Feature Learning via Generalized Rayleigh Quotients
MN-Diff: Diffusion Parameterized MoE-NCDE for Continuous Time Series Generation with Irregular Observations
Scalable Event Cloud Network for Event-based Classification
TRIM: Token-wise Attention-Derived Saliency for Data-Efficient Instruction Tuning
Hierarchical Filtering and Refinement Classification for Few-Shot Class-Incremental Learning
Bayes-inspired Integration of Pretrained Priors and Few-Shot Evidence for Few-Shot Classification
Activation-Free Backbones for Image Recognition: Polynomial Alternatives for Spatial and Channel Mixing
Transformers Learn the Optimal DDPM Denoiser for Multi-Token GMMs
RLVE: Scaling Up Reinforcement Learning for Language Models with Adaptive Verifiable Environments
A Decision-Theoretic View of Test-Time Training: When, How Far, and Which Directions to Adapt
SOPE: Situation-Aware and Statistically Indistinguishable Privacy Exfiltration for MCP-enabled Agents
Data Selection for Fine-tuning Vision Language Models via Cross Modal Alignment Trajectories
Time-PEFT: Temporal and Multichannel Complexity-Based Fine-Tuning for Time-Series Foundation Models
Parameters as Experts: Adapting Vision Models with Dynamic Parameter Routing for Dense Predictions
MER-DG: Modality-Entropy Regularization for Multimodal Domain Generalization
Belief Dynamics Reveal the Dual Nature of In-Context Learning and Activation Steering
Beyond the Final Answer: Evaluating the Reasoning Trajectories of Tool-Augmented Agents
Transfer Learning in High-dimensional Ising Models
APIC: Orthogonalized Neuro-Symbolic Modeling for Nonlinear Dissipative Dynamics
Learning Adaptive Perturbation-Conditioned Contexts for Robust Transcriptional Response Prediction
Return-to-Go Is More Than a Number: Q-Guided Alignment for Return-Conditioned Supervised Learning
Implicit Actor Critic Coupling via a Supervised Learning Framework for RLVR
Dismantling Pathological Shortcuts: A Causal Framework for Faithful LVLM Decoding
The Double-Edged Nature of the Rashomon Set for Trustworthy Machine Learning
Ultrafast On-Chip Online Learning via Spline Locality in Kolmogorov–Arnold Networks
Improving CLIP Adaptation by Breaking Tail Alignment for Source-Free Cross-Domain Few-Shot Learning
Return of Frustratingly Easy Unsupervised Video Domain Adaptation
Semi-Supervised Noise Adaptation: Transferring Knowledge from Noise Domain
Bayesian Meta-Learning with Expert Feedback for Task-Shift Adaptation through Causal Embeddings
From Kepler to Newton: Inductive Biases Guide Learned World Models in Transformers
MINT: Minimal Information Neuro-Symbolic Tree for Objective-Driven Knowledge-Gap Reasoning and Active Elicitation
Understanding Dynamic Compute Allocation in Recurrent Transformers
A Robust Optimization Guided Pruning Framework for Vision and Large Language Models
Position: AI Usage Policies Should Be Aligned with International Human Rights Law
Preference-Enhanced Reinforcement Learning for Pluralistic Image Inpainting
LiveOIBench: Can Large Language Models Outperform Human Contestants in Informatics Olympiads?
ThreadWeaver: Adaptive Threading for Efficient Parallel Reasoning in Language Models
ViTok-v2: Scaling Native-Resolution Autoencoders to 5B
DLM: Unified Decision Language Models for Offline Multi-Agent Sequential Decision Making
FOCUS & RePAIR: Mitigating Text Degeneration via Token-Level Guidance For Pruned Large Language Models
Future-Gain Guided Test-Time Learning for Large Language Models
Adversarial Flow Models
UAV$^2$: A Unified and Adaptive Scheduling Framework for UAV Autopilot System with Reinforcement Learning
Achieving Structurally Robust Gromov Wasserstein Distance via Adaptive Dual-Mask
A Tale of Two Problems: Multi-Task Bilevel Learning Meets Equality Constrained Multi-Objective Optimization
On the Optimization Trajectory of DeepWalk Embeddings
Allocating Variance to Maximize Expectation
MIRO: MultI-Reward cOnditioned pretraining improves T2I quality and efficiency
Fast Spectrally Sparse Signal Reconstruction via Jacobi-Preconditioned Gradient Descent
STLA: Spatiotemporal Lookahead Alignment for Post-Training Quantization
Diffusion-based learning framework for Constrained Nonconvex Optimization with Weighted Bootstrapped Refinement
Second-Order Bilevel Optimization with Accelerated Convergence Rates
From Optimization to Generalization under Heavy-Tailed Data: The Role of Gradient Clipping
FluxNet: Learning Capacity-Constrained Local Transport Operators for Conservative and Bounded PDE Surrogates
VAnim: Rendering-Aware Sparse State Modeling for Structure-Preserving Vector Animation
WIND: Weather Inverse Diffusion for Zero-Shot Atmospheric Modeling
Robust Causal Discovery in Real-World Time Series with Power-Laws
Flatness-Aware Stochastic Gradient Langevin Dynamics
Local Constrained Bayesian Optimization
Hide and Seek in Embedding Space: Geometry-based Steganography and Detection in Large Language Models
On the Interaction of Batch Noise, Adaptivity, and Compression, under $(L_0,L_1)$-Smoothness: An SDE Approach
Scaling Beyond Masked Diffusion Language Models
An In-Depth Study on Deep Learning Model Cloning
RMNP: Row-Momentum Normalized Preconditioning for Scalable Matrix-Based Optimization
Alignment-Sensitive Minimax Rates for Spectral Algorithms with Learned Kernels
PhaseAlign: Complex Phase Alignment for Stable Open-Vocabulary Semantic Segmentation
Loss-aware distributionally robust optimization via trainable optimal transport ambiguity sets
Scaling Generative Verifiers For Natural Language Mathematical Proof Verification And Selection
Softplus Attention with Re-weighting Boosts Length Extrapolation in Large Language Models
Clipped Q-Learning: Your Value Clipping Is Secretly A Robust Operator
Time Series, Vision, and Language: Exploring the Limits of Alignment in Contrastive Representation Spaces
From Drift to Coherence: Stabilizing Beliefs in LLMs
PretrainZero: Reinforcement Active Pretraining
Online Bayesian Experimental Design for Partially Observed Dynamical Systems
Doubly Regularized Markov Decision Processes for Robust Reinforcement Learning
Rethinking Sparse Mixture of Experts from a Unified Perspective
ProEval: Proactive Failure Discovery and Efficient Performance Estimation for Generative AI Evaluation
Flow Matching Calibration for Simulation-Based Inference under Model Misspecification
RED-HDP-HMM: Observation-Dependent Durations for Bayesian Nonparametric Sequential Models
SimpleGPT: Improving GPT via A Simple Normalization Strategy
Delving into Muon and Beyond: Deep Analysis and Extensions
Normalized Energy Models for Linear Inverse Problems
On the Salience of Low-Probability Tokens for AI-Generated Text Detection: A Multiscale Uncertainty Perspective
Symmetries in PAC-Bayesian Learning
Eigenvectors of Experts are Training-free Non-collapsing Routers
Efficient Adaptive Testing via Gradient Path Matching Subset Selection for AI Education
Bayesian-LoRA: Probabilistic Low-Rank Adaptation of Large Language Models
PromptDyG: Test-Time Prompt Adaptation on Dynamic Graphs
BALLAST: Bayesian Active Learning with Look-ahead Amendment for Sea-drifter Trajectories under Spatio-Temporal Vector Fields
Policy Search via Bayesian Optimization with Temporal Difference Gaussian Processes
MMPD-Bench: Bridging Multimodal Fission with Multi-Polarimetric Modalities Decomposition
Scalable Bayesian Inference for Nonlinear Conservation Laws
Extending Mean-Field Variational Inference via Entropic Regularization: Theory and Computation
Stochastic Gradient Variational Inference with Price's Gradient Estimator from Bures-Wasserstein to Parameter Space
Gaussian Mean Field Variational Inference can Overestimate Predictive Variance
How Does the Lagrangian Guide Safe Reinforcement Learning through Diffusion Models?
How Does the Pretraining Distribution Shape In-Context Learning? A Fundamental Trade-Off
TG-RAG: A Retrieval-Augmented Framework for Reasoning Guidance in Specialized Domains
AIR: Improving Agent Safety through Incident Response
OmniVL-Guard: Towards Unified Vision-Language Forgery Detection and Grounding via Balanced RL
SpeedCP: Fast Kernel-based Conditional Conformal Prediction
Robust Bayes-Assisted Conformal Prediction
Understanding Performance Collapse in Layer-Pruned Large Language Models via Decision Representation Transitions
Token-Free Hierarchical Indexing for RAG beyond LLM-based Summarization
Quantifying Temperature Scaling in Discrete Sequence (Language) Models
Constrained Multi-Objective Reinforcement Learning with Max-Min Criterion
CRPO: Character-centric Group Relative Policy Optimization for Role-aware Reasoning in Role-playing Agents
Position: The AI Imperative: Scaling High-Quality Peer Review in Machine Learning
Position: Multi-Agent Explainability Needs Contracts Before Methods
EntRAG: Entity-Centric Retrieval-Augmented Generation for Knowledge-based Visual Question Answering
All Circuits Lead to Rome: Rethinking Functional Anisotropy in Circuit and Sheaf Discovery for LLMs
Hierarchical ODE: Learning Continuous-Time Physical Prototypes for Early Link Failure Detection
mHC: Manifold-Constrained Hyper-Connections
SHAP-Guided Kernel Actor-Critic for Explainable Reinforcement Learning
Towards High-Fidelity CAD Generation via LLM-Driven Program Generation and Text-Based B-Rep Primitive Grounding
Expanding the AI Evaluation Toolbox with Statistical Models
Reconstruction Outcomes Look Similar but Processes Differ: Improving Context Consistency and Coverage in Graph Masked Auto-Encoder
RelaxFlow: Text-Driven Amodal 3D Generation
Steering Large Language Models through the DMTA Cycle: Structure-Based Drug Design via Knowledge-Driven Bi-Level Thompson Sampling
Towards Steering without Sacrifice: Principled Training of Steering Vectors for Prompt-only Interventions
Activation Oracles: Training and Evaluating LLMs as General-Purpose Activation Explainers
Evaluating Contextual Illegality: AI Compliance in Corporate Law Scenarios
AgentNoiseBench: Benchmarking Robustness of Tool-Using LLM Agents Under Noisy Condition
Sparse Relaxed-Lasso Steering: Automatic Sparse-Autoencoder Feature Selection for Precise Image Editing
Conflicting Biases at the Edge of Stability: Norm versus Sharpness Regularization
PolySAE: Modeling Feature Interactions in Sparse Autoencoders via Polynomial Decoding
Is Your LLM Overcharging You? Tokenization, Transparency, and Incentives
Discretized Density-Guided Source-Free Adaptation for Continuous Targets
Position: Sustainable Open-Source AI Requires Tracking the Cumulative Footprint of Derivatives
PACE: Proactive Agent-Level Admission Control for Efficient Agentic Batch Inference
FairGB: A Fair Granular-Ball Generation Method for Data Classification
Position: State-of-the-Art Claims Require State-of-the-Art Evidence
DeepHA: Scaling Action Chains Elicits Deep Hierarchical Agents
Capturing Gaze Shifts for Guidance: Cross-Modal Fusion Enhancement for VLM Hallucination Mitigation
OpenHA: A Series of Open-Source Hierarchical Agentic Models in Minecraft
Provably Adaptive Linear Approximation for the Shapley Value and Beyond
MAnchors: Memorization-Based Acceleration of Anchors via Rule Reuse and Transformation
Analytic Bijections for Smooth and Interpretable Normalizing Flows
Probabilistic Performance Guarantees for Multi-Task Reinforcement Learning
Characterization of Gaussian Universality Breakdown in High-Dimensional Empirical Risk Minimization
FedSSM: State Space Model-based Proactive Inference for Heterogeneous Multimodal Federated Learning
Ensembling Sparse Autoencoders
Priority-Aware Shapley Value
Generative Neural Operators through Diffusion Last Layer
TACTIC: Task-Aware Sparse Coordination Graphs for Multi-Task Multi-agent Reinforcement Learning
Stability and Generalization of Nonconvex Optimization with Heavy-Tailed Noise
$\texttt{ShaplEIG}$: Bayesian Experimental Design for Shapley Value Estimation
Target-Agnostic Calibration under Distribution Shift with Frequency-Aware Gradient Rectification
Beyond Tokens: Enhancing RTL Quality Estimation via Structural Graph Learning
Position: Machine Learning Research Should Be Guided by Explicit, Pluralistic Models of Human Purpose
Localize-and-Stitch: Efficient Model Merging via Sparse Task Arithmetic
FedSDR: Federated Self-Distillation with Rectification
Regularization in the Axiomatic Approach to Learning from Human Preferences
UniRTL: Unifying Code and Graph for Robust RTL Representation Learning
From Parameters to Data: A Task-Parameter-Guided Fine-Tuning Pipeline for Efficient LLM Alignment
CaliDist: Calibrating Large Language Models via Behavioral Robustness to Distraction
CAReDiO: Enhancing Cultural Alignment of LLM via Representativeness and Distinctiveness Guided Data Optimization
Scheduling LLM Inference with Uncertainty-Aware Output Length Predictions
Position: Spatial Fairness: Foundations, Pitfalls, and a Path Forward
Exposing Hidden Biases in Text-to-Image Models via Automated Prompt Search
See First, Reason Later: Mutual Information-Guided Reinforcement Learning for Vision-Language Models
Preference-Modulated Structural Attention for Multi-Objective Combinatorial Optimization
Hom-PGD+: Fast Reparameterized Optimization over Non-convex Ball-Homeomorphic Set
Large Language Models Develop Novel Social Biases Through Adaptive Exploration
Position: The Term “Machine Unlearning” Is Overused in LLMs
Tempora: Characterising the Time-Contingent Utility of Online Test-Time Adaptation
Position: Stop Automating Peer Review Without Rigorous Evaluation
Orchestrating Spatial Semantics via a Zone-Graph Paradigm for Intricate Indoor Scene Generation
Position: Preparing for AI Systems That Deceive Developers
Robust Harmful Features Under Jailbreak Attacks: Mechanistic Evidence from Attention Head Specialization in Large Language Models
Step-Level Sparse Autoencoder for Reasoning Process Interpretation
ForceForget: Reinforcement Concept Removal for Enhancing Safety in Text-to-Image Models
Lookahead-GCG: Improving Multi-Model Gradient-Based Jailbreaking Attacks via Nesterov Momentum
Chasing Moving Targets with Online Self-Play Reinforcement Learning for Safer Language Models
Attacking Gray-Box Large Vision-Language Models with Adaptive SVD-Structured Adversarial Alignment
Rethinking 1-bit Optimization Leveraging Pre-trained Large Language Models
Position: Preregister Experiments with AI Agents
A Close Look at Negative Label Guided Out-of-distribution Detection in Pre-trained Vision-Language Models
From 2D Grids to 1D Tokens: Reforming Shared Representations for Multimodal Image Fusion
Frontier Models Can Take Actions at Low Probabilities
Contrastive Diffusion Alignment: Learning Structured Latents for Controllable Generation
Generalized Schrödinger Bridge on Graphs
Speculative Safety Honeypot: Toward Proactive Defense Against Multi-turn Agent Attacks
ECSEL: Explainable Classification via Signomial Equation Learning
Efficient LLM Moderation with Multi-Layer Latent Prototypes
The Trojan Knowledge: Bypassing Commercial LLM Guardrails via Harmless Prompt Weaving and Adaptive Tree Search
From Parameter Dynamics to Risk Scoring: Quantifying Sample-Level Safety Degradation in LLM Fine-tuning
SCOPE and SCION: Benchmark and Method for Ontology Induction and Fusion from Text
Federated Variational Preference Alignment with Gumbel-Softmax Prior for Personalized User Preferences
Dynamic High-Dimensional Facility Location with Low Recourse
FormalRx: Rectify and eXamine Semantic Failures in Autoformalization
Breaking Multi-Task Curse: Reward-Weighted Evolution for Black-Box Many-Task Optimization
Training-Free Rate-Distortion-Perception Traversal With Diffusion
Mechanistic Anomaly Detection via Functional Attribution
How Should Transformers Represent Numeric Values in Electronic Health Records?
Building Reliable Long-Form Generation via Hallucination Rejection Sampling
RADE: Unbiased Random Add-Drop Edge as a Regularizer
LUCID: Attention with Preconditioned Representations
Detecting Fluent Optimization Based Adversarial Prompts via Sequential Entropy Changes
Latent-Guided Cooperative Energy-Based Models
Learning in the Fisher Subspace: A Guided Initialization for LoRA Fine-Tuning
An Empirical Study of Memory Poisoning Defenses for LLM Agents
ZeroUnlearn: Few-Shot Knowledge Unlearning in Large Language Models
Sparse Bayesian Deep Functional Learning with Structured Region Selection
Understanding Self-Supervised Learning via Latent Distribution Matching
When the Prompt Becomes Visual: Vision-Centric Jailbreak Attacks for Large Image Editing Models
ASIR: Steganography for Diffusion Models via Antipodal Sampling and Iterative Recovery
Privacy Risks of Agentic Inferential Capabilities in Data Linkage Attacks
RepetitionCurse: Measuring and Understanding Router Imbalance in Mixture-of-Experts LLMs under DoS Stress
Visual Implicit Autoregressive Modeling
Models Under SCOPE: Scalable and Controllable Routing via Pre-hoc Reasoning
Anti-Backdoor Coreset Selection via Cumulative Entropy
ProphetKV: User-Query-Driven Selective Recomputation for Efficient KV Cache Reuse in Retrieval-Augmented Generation
Thinking in Scales: Accelerating Gigapixel Pathology Image Analysis via Adaptive Continuous Reasoning
SHARP-Q: Spectral Hessian Alignment and Rectification for Post-training Quantization
IBMA: Information Bottleneck-Based Multimodal Alignment
Adaptive Probe-based Steering for Robust LLM Jailbreaking
PragLocker: Protecting Agent Intellectual Property in Untrusted Deployments via Non-Portable Prompts
FUSE: Full‑spectrum Unlearnable Examples via Spectral Equalization
CausalArmor: Efficient Indirect Prompt Injection Guardrails via Causal Attribution
RADAR: Defending RAG Dynamically against Retrieval Corruption
Scam2Prompt: A Scalable Framework for Auditing Malicious Scam Endpoints in Production LLMs
SPR-RAFT: Parameter-Efficient Regression-Aware Fine-Tuning for Biomedical LLM Regression
Structured Multi-step Jailbreaking under a Hamiltonian Generative Formulation
Position: Irresponsible AI: big tech’s influence on AI research and associated impacts
Falsifying Sparse Autoencoder Reasoning Features in Language Models
Neural Minimum Weight Perfect Matching for Quantum Error Codes
RECAST: Model Reconstruction via Counterfactual-Aware Wasserstein Geometry under Limited Data
Position: The Turing-Completeness of Real-World Autoregressive Transformers Relies Heavily on Context Management
De-attribute to Forget for LLM Unlearning
Incentivizing Truthfulness and Collaborative Fairness in Bayesian Learning
From Pixels to Tokens: A Systematic Study of Latent Action Supervision for Vision-Language-Action Models
Unsupervised Camouflaged Object Detection with Dual-Eigenvector Spectral Pseudo-Labeling and Contrastive Refinement
Factored Gossip DiLoCo: Reducing Blocking Communication within DiLoCo
Q-Sched: Pushing the Boundaries of Few-Step Diffusion Models with Quantization-Aware Scheduling
Balanced LoRA: Removing Parameter Invariance to Accelerate Convergence
Fast Inverse Lithography via GRPO Reinforced Flow Matching
Kalman Linear Attention: Parallel Bayesian Filtering For Efficient Language Modeling and State Tracking
Are LLM Evaluators Really Narcissists? Sanity Checking Self-Preference Evaluations
Position: RL Should Be Used to Adjust Foundation Models, NOT Abused
Being More Lightweight and Practical: Mini-sized Contrastive Learning Pre-trained Models for Fine-grained Traffic Task
Neural Thickets: Diverse Task Experts Are Dense Around Pretrained Weights
Synthesizing Multimodal Geometry Datasets from Scratch and Enabling Visual Alignment via Plotting Code
Bringing Code ALIVE: Optimizing Interactive Frontend Mini-Games via Automated Play and Reinforcement Learning at Scale
Active Reasoning Vision-Language Model via Sequential Experimental Design
Motion Planning in Compressed Representation Spaces
Improving Sampling for Masked Diffusion Models via Information Gain
Random Process Flow Matching: Generative Implicit Representations of Multivariate Random Fields
TAG: Tangential Amplifying Guidance for Hallucination-Resistant Sampling
Designing noise schedules for diffusion models with spectral analysis
A Narrowing Geometry in Contaminated Reasoning
Addressing Instrument-Outcome Confounding in Mendelian Randomization through Representation Learning
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
FrameOracle: Learning What to See and How Much to See in Videos
Towards a Holistic Understanding of Selection Bias for Causal Effect Identification
SafeSeek: Universal Attribution of Safety Circuits in Language Models
Adaptive Generation of Bias-Eliciting Questions for LLMs
Estimation of Treatment Effects Under Nonstationarity via the Truncated Policy Gradient Estimator
4RC: 4D Reconstruction via Conditional Querying Anytime and Anywhere
AutoBaxBuilder: Bootstrapping Code Security Benchmarking
Infinite-dimensional generative diffusions via Doob's h-transform
Temporal Self-Rewarding Language Models: Decoupling Chosen-Rejected via Past-Future
Entropic Mirror Monte Carlo
Dynamic Symmetric Point Tracking: Tackling Non-ideal Reference in Analog In-memory Training
Position: Adopting AI in Practice Does Not Guarantee the Productivity Boost
Categorical Reparameterization with Denoising Diffusion models
Bayesian Rain Field Reconstruction using Commercial Microwave Links and Diffusion Model Priors
Physics-Guided Motion Loss for Video Generation Model
BioAgent Bench: An AI Agent Evaluation Suite for Bioinformatics
Variance-Reduced Zeroth-Order Langevin Dynamics for Non-Log-Concave Black-Box Sampling and Inverse Problems
ContrastiveCFG: Guiding Diffusion Sampling by Contrasting Positive and Negative Concepts
Temporal Score Rescaling for Temperature Sampling in Diffusion and Flow Models
CoCoEdit: Content-Consistent Image Editing via Region Regularized Reinforcement Learning
Inference-Time Forward-Process Alignment in Diffusion Models
Credible Information Subset Decomposition: An End-to-End Multi-fidelity Learning Model by Modeling Label Information
A Unified Density Operator View of Flow Control and Merging
SymSpectra: Symmetric Information Bottleneck Framework for Molecular Structure Recognition under Imbalanced Settings
AES: Curing Optimizer Blindness in Long-Tailed Recognition via State-Aware Correction
Control Consistency Losses for Diffusion Bridges
Improving LLM-Based Recommenders with Conservative Generative Flow Networks
Crisp: A Spectral-Based Interaction Strategy for Multivariate Time Series Forecasting
The Realignment Problem: When Right becomes Wrong in LLMs
Reconstructing Template-Memorized Images from Natural Prompts
Multimarginal flow matching with optimal transport potentials
StableVLA: Towards Robust Vision-Language-Action Models without Extra Data
AvAtar: Learning to Align via Active Optimal Transport
Rényi Diffusion Models
Boosting Video Diffusion Models via Masked Autoencoders as Tokenizers
Alignment-Guided Score Matching for Text-to-Image Alignment in Diffusion Models
Stage-wise Distortion–Perception Traversal in Zero-shot Inverse Problems with Diffusion Models
Contextualized Visual Personalization in Vision-Language Models
Kronecker Generative Networks: A General Neural Architecture for Parameter-Efficient Learning Across Classification Tasks
FakeWorld 1.0: An Omni modal Benchmark for Fake Media and Content
Variable-Length Tokenization via Learnable Global Merging for Diffusion Transformers
Label-Guided Representation Learning for Incomplete Multi-View Multi-Label Classification
Neural Quantum States in Mixed Precision
Not All Rollouts are Useful: Down-Sampling Rollouts in LLM Reinforcement Learning
Position: Agent Should Invoke External Tools ONLY When Epistemically Necessary
ML-Agent: Reinforcing LLM Agents for Autonomous Machine Learning Engineering
MCP-Persona: Benchmarking LLM Agents on Personalized MCP Tools and Tasks
The Tell-Tale Norm: $\ell_2$ Magnitude as a Signal for Reasoning Dynamics in Large Language Models
Learning to Evict from Key-Value Cache
NEMO: Execution-Aware Optimization Modeling via Autonomous Coding Agents
When Model Merging Breaks Routing: Training-Free Calibration for MoE
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
Adaptive Symmetry Discovery for Dynamical System Identification
Unitary Convolutions for Message-passing and Positional Encodings on Directed Graphs
Scaling the Scaling Logic: Agentic Meta-Synthesis of Logic Reasoning
OPUS: Towards Efficient and Principled Data Selection in Large Language Model Pre-training in Every Iteration
Neural Feature Geometry Evolves as Discrete Ricci Flow
Mind Dreamer: Untethering Imagination via Active Counterfactual Reasoning on Latent Manifolds
Deterministic Differentiable Structured Pruning for Large Language Models
Agentic Proposing: Enhancing Large language Model Reasoning via Compositional Skill Synthesis
Breaking the Echo Chamber: A Dynamic Ensemble Pruning Perspective on MoE
OmniSIFT: Modality-Asymmetric Token Compression for Efficient Omni-modal Large Language Models
Cluster-Aware Causal Mixer for Online Anomaly Detection in Multivariate Time Series
Breaking Dual Bottlenecks: Evolving Unified Multimodal Models into Self-Adaptive Interleaved Visual Reasoners
SelfJudge: Faster Speculative Decoding via Self-Supervised Judge Verification
Token Sparse Attention: Efficient Long-Context Inference with Interleaved Token Selection
Inverse Depth Scaling From Most Layers Being Similar
A geometric relation of the error introduced by sampling a language model's output distribution to its internal state
SERA: Soft-Verified Efficient Repository Agents
Polishing-Only Policies in Peer Reviews are Currently Not Enforceable
Towards Multimodal Large Language Models with Both Training and Inference Efficiency
Inference Time Optimization with Confidence Dynamics
Learnability-Informed Fine-Tuning of Diffusion Language Models
The Unlearnability Phenomenon in RLVR for Language Models
Mitigating Manifold Departure: Uncertainty-aware Subspace Rectification for Trustworthy MLLM Decoding
Multi-Head LatentMoE and Head Parallel: Communication-Efficient and Deterministic MoE Parallelism
Reward Modeling from Natural Language Human Feedback
GEPC: Group-Equivariant Posterior Consistency for Out-of-Distribution Detection in Diffusion Models
Retaining by Doing: The Role of On-Policy Data in Mitigating Forgetting
Mechanistic Data Attribution: Tracing the Training Origins of Interpretable LLM Units
MEDUSA: Motion Elimination in Diffusion Using Spectral Attack
ConFu: Contemplate the Future for Better Speculative Sampling
Proact-VL: A Proactive VideoLLM for Real-Time AI Companions
Optimizing Network Simulation: Enhancing Performance Prediction Accuracy via Neural Architecture Search
Physics-Informed Distillation of Diffusion Models for PDE-Constrained Generation
daVinci-Dev: Agent-native Mid-training for Software Engineering
Enhancing LLM Training via Spectral Clipping
Bring Future Vision: Dynamic Computation Allocation Guided by Lightweight Feature Forecaster
Relative Entropy Estimation in Function Space: Theory and Applications to Trajectory Inference
Orthogonal Hierarchical Decomposition for Structure-Aware Table Understanding with Large Language Models
RePo: Language Models with Context Re-Positioning
Safe Reinforcement Learning with Preference-based Constraint Inference
SARSteer: Safeguarding Large Audio Language Models via Safe-Ablated Refusal Steering
Amortized Variational Inference for Partial-Label Learning: A Probabilistic Approach to Label Disambiguation
Bi-Anchor Interpolation Solver for Accelerating Generative Modeling
Optimality of FSQ tokens for continuous diffusion for categorical data with application to text-to-speech
LLM-Guided Diagnostic Evidence Alignment for Medical Vision–Language Pretraining under Limited Pairing
Improving Backward Conformal Prediction via Non-Conformity Score Transformation
Robustifying Vision-Language Models via Test-Time Prompt Adaptation
How to Correctly Report LLM-as-a-Judge Evaluations
Let the Prototype Guide You: Robust Aggregation of Sparse Multi-Class Annotations via Annotator Prototype Learning
Path-Decoupled Hyperbolic Flow Matching for Few-Shot Adaptation
One Tool Is Enough: Reinforcement Learning of LLM Agents for Repository-Level Code Navigation
Language-based Trial and Error Falls Behind in the Era of Experience
Dissecting Post-Training: Uncovering the Complementary Roles of SFT and RL for Document Parsing
Representational Curvature Shapes Behavioral Uncertainty in Large Language Models
What Linear Probes Miss: Multi-View Probing for Weight-Space Learning
DecepChain: Inducing Deceptive Reasoning in Large Language Models
Immuno-VLM: Immunizing Large Vision-Language Models via Generative Semantic Antibodies for Open-World Trustworthiness
Learning to Decode Against Compositional Hallucination in Video Multimodal Large Language Models
CE$^4$L: Continual Ego, Exo, and Ego-Exo Learning
Edit-Based Refinement for Parallel Masked Diffusion Language Models
SAEmnesia: Erasing Concepts in Diffusion Models with Supervised Sparse Autoencoders
Position: RL Researchers Need to Distinguish Between Solving Simulators and Using Simulators as a Proxy
More Sail than Ballast: Addressing Harmful Knowledge Leakage in the Expansive Reasoning Space of LRMs
Native Active Perception as Reasoning for Omni-Modal Understanding
Guidance: Sentence-Level Citation Enforcement via Prefix-Tail Guidance during LLM Decoding
AdamO: A Collapse-Suppressed Optimizer for Offline RL
Probing Newtonian Mechanics in Video Generative Models with Real Physical Systems
DreamID-Omni: Unified Framework for Controllable Human-Centric Audio-Video Generation
Black-Box Combinatorial Optimization with Order-Invariant Reinforcement Learning
Test-Time Detoxification without Training or Learning Anything
Optimizing Inference-Time Compute for Medical Reasoning via Uncertainty Quantification
Periodic Bayesian Flow Networks with Additive Accuracy
Masks Can Be Distracting: On Context Comprehension in Diffusion Language Models
FrontierCS: Evolving Challenges for Evolving Intelligence
Learning Randomized Reductions
Transporting Task Vectors across Different Architectures without Training
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
FIRE-Bench: Evaluating Agents on the Rediscovery of Scientific Insights
Easier to Judge than to Find: Predicting In-Context Learning Success for Demonstration Selection
ScaleSim: Serving Large-Scale Multi-Agent Simulation with Invocation Distance-Based Memory Management
PLoRA: Efficient Concurrent LoRA Training for Large Language Models
Effective Model Pruning : Measuring the Redundancy of Model Components
Representational Similarity and Model Behavior in Multi-Agent Interaction
STAR: Rethinking MoE Routing as Structure-Aware Subspace Learning
HypRAG: Hyperbolic Dense Retrieval for Retrieval Augmented Generation
Mosaic: Unlocking Over 30$\times$ Context Length for Diffusion LLMs Inference via Global Memory Planning and Dynamic Peak Taming
Push, Pop, Parallelize: Stack-Augmented Linear Attention via the Delta Rule
Alignment-Aware Decoding
GRPO is Secretly a Process Reward Model
SuperHype: Hypergraph Generation via Graph-Superposition Decomposition
Smoothness Errors in Dynamics Models and How to Avoid Them
ECHO: Elastic Speculative Decoding with Sparse Gating for High-Concurrency Scenarios
Scalable Topology-Preserving Graph Coarsening: Concepts and Algorithms
Compress then Merge: From Multiple LoRAs into One Low-Rank Adapter
MIND: Multi-rationale INtegrated Discriminative Reasoning Framework for Multi-modal Large Models
Attention Projection Mixing with Exogenous Anchors
InftyThink+: Effective and Efficient Infinite-Horizon Reasoning via Reinforcement Learning
On the Convergence of Steepest Descent and Adaptive Gradient Methods under Non-Uniform Smoothness
Scout Before You Attend: Sketch-and-Walk Sparse Attention for Efficient LLM Inference
SLAP: The Semantic Least Action Principle for Variational Video-Language Modeling
HiDe: Rethinking The Zoom-IN method in High Resolution MLLMs via Hierarchical Decoupling
Position Is All You Need: A Free Lunch Token Compression Strategy for MLLM-based Referring Expression Segmentation
Efficiently Learning Drifting Halfspaces with Massart Noise
Mining Useful General Data for Low-Resource Domain Adaptation
AdaHC: Accelerating Multi-Token Prediction with Adaptive Head Chunking with Pipeline Parallelism
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
Expressivity-Efficiency Tradeoffs for Hybrid Sequence Models
Robust-U1: Can MLLMs Self-Recover Corrupted Visual Content for Robust Understanding?
How can we assess human-agent interactions? Case studies in software agent design
iGRPO: Fast Online RL for Flow Matching Model with Dense Reward
Learning Structured Reasoning via Tractable Trajectory Control
BPL: Generalizable Deepfake Detection via Bias-only Pair-aware Learning
SWE-Bench Pro: Can AI Agents Solve Long-Horizon Software Engineering Tasks?
Biologically plausible heavy-tailed connectivity enhances generalizations on cognitive tasks in recurrent neural networks
Multi-Objective Preference Optimization: Improving Human Alignment of Generative Models
Consistent Zero-Shot Imitation with Contrastive Goal Inference
Parallel-Probe: Towards Efficient Parallel Thinking via 2D Probing
Learning-Guided Integration Contours Construction for Fast Large-Scale Generalized Eigensolvers
Controllable Molecule Generation via Sparse Representation Editing: An Interpretability-Driven Perspective
Incomplete Multi-View Clustering via Neighborhood-Conditioned Diffusion
LIMSSR: LLM-Driven Sequence-to-Score Reasoning under Training-Time Incomplete Multimodal Observations
Investigating Component Contributions in Multi-Agent ML Systems
Geodesic Calculus on Implicitly Defined Latent Manifolds
RELO: Reinforcement Learning to Localize for Visual Object Tracking
Knowing the Unknown: Interpretable Open-World Object Detection via Concept Decomposition Model
Which Reasoning Traces Are Worth Generating Further? Data Curation for Training Reasoning Models
Resolving Blind Inverse Problems under Dynamic Range Compression via Structured Forward Operator Modeling
Position: Benchmarks Do Not Measure Deployment Readiness in Clinical AI
Weakly Supervised Cross-Modal Learning for 4D Radar Scene Flow Estimation
WorldCache: Accelerating World Models for Free via Heterogeneous Token Caching
GOCM: Single-Step Graph Outlier Synthesis via Origin Consistency Model
Do Natural Language Interpretability Methods Convey Privileged Information?
CauseCollab: Causal Unified and Modality-Agnostic Network for Heterogeneous Collaborative Perception
Transformers with RL or SFT Provably Learn Sparse Boolean Functions, But Differently
Offline Preference Optimization for Rectified Flow with Noise-Tracked Pairs
CodeMamba: Shifting from Target Semantics to Self-Supervised Background Manifold Learning for Singularity Detection in Infrared Sequences
Position: Responsible Practices and Model Performance are Not Competing Goals
ImpQuant: Fine-Grained Importance-Aware Quantization for Large Vision-Language Models
Toward Identifiable Sparse Autoencoders
Geometry-Aware Dataset Condensation for Diffusion Model Training
RN-D: Discretized Categorical Actors with Regularized Networks for On-Policy Reinforcement Learning
Learning Gaussian Mixture-distributed Prototypes for 3D Scene Graph Generation from RGB-D Sequences
iTryOn: Mastering Interactive Video Virtual Try-On with Spatial-Semantic Guidance
GameVerse: Can Vision-Language Models Learn from Video-based Reflection?
Think Twice Before You Act: Protecting LLM Agents Against Tool Description Poisoning via Isolated Planning
Arboreal Neural Network
Diversity-Preserved Distribution Matching Distillation for Fast Visual Synthesis
Pair2Scene: Learning Local Object Relations for Procedural Scene Generation
MoVie: Multimodal Video Compression with Text Guidance
Multi-scale Explainer for Graph Neural Networks
Nested birth-death processes are competitive with parameter-heavy neural networks as time-dependent models of protein evolution
EEG-Based Multimodal Learning via Hyperbolic Mixture-of-Curvature Experts
Flash-GRPO: Efficient Alignment for Video Diffusion via One-Step Policy Optimization
Semi-LAR: Semi-supervised Contrastive Learning with Linear Attention for Removal of Nighttime Flares
Bulk-Calibrated Credal Ambiguity Sets: Fast, Tractable Decision Making under Out-of-Sample Contamination
Ask Less, See More: Communication-Conditioned Token Pruning for Vehicle-to-Vehicle Cooperative Autonomous Driving with Multimodal Large Language Models
Decoupling Variance and Scale-Invariant Updates in Adaptive Gradient Descent for Unified Vector and Matrix Optimization
Self-Supervised Flow Matching for Scalable Multi-Modal Synthesis
Bend the Basics: Degradation-Aware Deformable Tokenization for All-in-One Image Restoration
Reward Redistribution for CVaR MDPs using a Bellman Operator on L-infinity
OServe: Accelerating LLM Serving via Spatial-Temporal Workload Orchestration
Learning Partial Concept Classes and Universal Rates Under Massart Noise
High-Probability Convergence Guarantees of Decentralized SGD
DITING: A Weak Degradation Listener for Battery Lifetime Early Prediction
MTNL: A Unified Modeling Perspective for Enhancing Tensor Network Learning
Exploring Accurate and Transparent Domain Adaptation in Predictive Healthcare via Concept-Grounded Orthogonal Inference
Structured 4D Latent World Model for Robot Planning
Posterior Mismatch Matters: Adversarial Training for Long-Tailed Robustness
Rethinking the Reranker: Boundary-Aware Evidence Selection for Robust Retrieval-Augmented Generation
Trajectory Stitching for Solving Inverse Problems with Flow-Based Models
Many Needles in a Haystack: Active Hit Discovery for Perturbation Experiments
Quantifying the Effect of Noise in Language Generation
Bad Seeing or Bad Thinking? Rewarding Perception for Multimodal Reasoning
Q-DiT4SR: Exploration of Detail-Preserving Diffusion Transformer Quantization for Real-World Image Super-Resolution
Are Common Substructures Transferable? Understanding Transferability in Graph Pretraining under Riemannian Geometry
GASS: Geometry-Aware Spherical Sampling for Disentangled Diversity Enhancement in Text-to-Image Generation
Scientific logicality enriched methodology for LLM reasoning: A practice in physics
From Statics to Dynamics: Physics-Aware Image Editing with Latent Transition Priors
Stochastic Neural Ray Tracing for Radio Frequency Channel Modeling
Position: We Need Large Language Models Optimized For Our Well-Being
FlowNar: Scalable Streaming Narration for Long-Form Videos
Tabero: Learning Gentle Manipulation with Closed-Loop Force Feedback from Vision, Touch, and Language
Hearing Without Noticing? Attention-Aware Stealthy Black-box Adversarial Audio Attacks
Towards Hierarchy–Uniformity Equilibrium: Recovering Semantic Depth in Hypergraph Contrastive Learning
Does a Hybrid Space-Aware Randomized Defense Improve Empirical and Certified Adversarial Robustness?
MAS-Architect: Declarative Multi-Agent System Design via Separation of Concerns
UCPO: Uncertainty-Aware Policy Optimization
Creat3r: Confidence Reaggregation for Exploration-aware Active 3D Reconstruction
T2AV-Compass: Towards Unified Evaluation for Text-to-Audio-Video Generation
Revisiting Uncertainty: On Evidential Learning for Partially Relevant Video Retrieval
TPGDiff : Hierarchical Triple-Prior Guided Diffusion for Image Restoration
The Accumulation of Score Estimation Error in Diffusion Models
LangPrecip: Language-Aware Multimodal Precipitation Nowcasting
DecomPose: Disentangling Cross-Category Optimization Contention for Category-Level 6D Object Pose Estimation
Revisiting Coding-Based Approaches to Overcome the Curse of Dimensionality in Learning-Based Watermarking
HieraScaffold: Learning Compact Hierarchical Representations for Scalable 4D LiDAR Generation
Predicting Dynamic Stability Landscapes in Synchronization Networks
GeoLoom: High-quality Geometric Diagram Generation from Textual Input
Active Exploring like a Pigeon: Reinforcing Spatial Reasoning via Agentic Vision-Language Models
E²I-VRWKV: Explicit EPI-Representation and Interaction-Aware Vision-RWKV for Light Field Semantic Segmentation
Overcoming PINNs Failure Modes In High Dimension With Low-Rank Fourier Sum
Bridging the Perceptual Gap: Residual-Enhanced Downscaling and Manifold-Aware Perception Alignment Adaptation for NR-IQA
StitchCUDA: An Automated Multi-Agents End-to-End GPU Programing Framework with Rubric-based Agentic Reinforcement Learning
GO-PRE：Goal-Oriented Next-Best-View Selection via Predictive Rendering Entropy for Active 3D Reconstruction
REAL: Regression-Aware Reinforcement Learning for LLM-as-a-Judge
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
Position: Interestingness is an Inductive Heuristic for Future Compression Progress
From Extrinsic to Intrinsic: Geodesic-Guided Representation Learning for 3D Geometric Data
ProConMV: Provenance-Enabled Conceptual Framework for Interpretable Multi-View Diabetic Retinopathy Diagnosis
scCBGM: Single-Cell Editing via Concept Bottlenecks
Position: Scale is a False Promise for Endangered Languages
MedCRP-CL: Continual Medical Image Segmentation via Bayesian Nonparametric Semantic Modality Discovery
Learning to Memorize with Attributive and Associative Memory for Online Test-Time Adaptation of Vision-Language Models
Are We Overconfident in Models and Results for Semi-Supervised 3D Medical Image Segmentation?
Conditional Diffusion Sampling
Unifying Masked Diffusion Models with Various Generation Orders and Beyond
AdaSCALE: Adaptive Scaling for OOD Detection
High-Fidelity ANN-to-SNN Conversion via Closed-Loop CKA Distillation
On the Infinite Width and Depth Limits of Predictive Coding Networks
SEM-CTRL: Semantically Controlled Decoding
SEER: Transformer-based Robust Time Series Forecasting via Automated Patch Enhancement and Replacement
DAG: A Dual Correlation Network for Time Series Forecasting with Exogenous Variables
Omni-fMRI: A Universal Atlas-Free fMRI Foundation Model
Multi-Task Bayesian In-Context Learning
Rational Neural Networks have Expressivity Advantages
Factored Value Functions for Graph-Based Multi-Agent Reinforcement Learning
Bridging Time and Frequency: A Joint Modeling Framework for Irregular Multivariate Time Series Forecasting
Self-Supervised Foundation Model for Calcium-imaging Population Dynamics
Alignment between Brains and AI: Evidence for Convergent Evolution across Modalities, Scales and Training Trajectories
Unsupervised Neural Langevin Sampler for Mixed Integer Linear Programming
Rectified LpJEPA: Joint-Embedding Predictive Architectures with Sparse and Maximum-Entropy Representations
Cross-Chirality Generalization by Axial Vectors for Hetero-Chiral Protein-Peptide Interaction Design
Generalized Boundary FDR Control under Arbitrary Dependence: An Approach on Closure Principle
Trees to Flows and Back: Unifying Decision Trees and Diffusion Models
Dynamic Compression Flows for Neuroscience Data
Image-to-Brain Signal Generation for Visual Prosthesis with CLIP Guided Multimodal Diffusion Models
Position: Virtual Cells Need Context, Not Just Scale
$\texttt{IDEAS}$: Interpretability Driven Evolutionary Approach for the Design of Biological Sequences
Learning Multi-Scale Hypergraph for High-Order Brain Connectivity Analysis
Optimal Transport Group Counterfactual Explanations
Global Credit Assignment via Dynamical Criticality
Frequency Matching in Spiking Neural Networks for mmWave Sensing
VBA: Vector Bundle Attention for Intrinsically Geometric Representation Learning
Abstraction Induces the Brain Alignment of Language and Speech Models
Linguistic Properties and Model Scale in Brain Encoding: From Small to Compressed Language Models
Scaling Vision Transformers for Functional MRI with Flat Maps
Modeling Long-Tail Relations in the Operating Room via In-Context Multimodal Learning
Positional Encoding for Spiking Transformers
Origo: Physically Interpretable Multi-Physics PDE Pre-training through Neural Operator Splitting
Discriminative Mixture-of-Experts on Graphs with Reliable Expert Fusion
Teaching Models to Teach Themselves: Reasoning at the Edge of Learnability
NOMAD: Lifelong Trajectory Planning via Non-Parametric Bayesian Memory-Adaptive Diffusion Experts
Geometry-Guided Modeling of Foundation Features Enables Generalizable Object Shape Deformation Learning
The Cylindrical Representation Hypothesis for Language Model Steering
Convergence Rate Analysis of the AdamW-Style Shampoo: Unifying One-sided and Two-Sided Preconditioning
Cross-Embodiment Robot Foundation World Models with Latent Actions
Terminal Dimension Reduction for Time Series with Applications
Verbalized Bayesian Persuasion
Scalable and Stable Estimation of Amari $\alpha$-Divergence using Random Fourier Features
Think Less, Act Early: Reinforced Latent Reasoning with Early Exit in Vision-Language-Action Models
CofactGVR: Counterfactual Intervention for Grounded Visual Reasoning
MetaStreet: Semi-Supervised Multimodal Learning for Street-Level Socioeconomic Prediction
Less Token, More Signal: MoE Expert Pruning via Critical Token Selection
Demystifying Action Space Design for Robotic Manipulation Policies
Event2Vec: Processing neuromorphic events directly by representations in vector space
PhaseCoder: Microphone Geometry-Agnostic Spatial Audio Understanding for Multimodal LLMs
Gram2Token: Enabling Run-time GPU-Native Grammar-Constrained Decoding for LLMs
The Label Horizon Paradox: Rethinking Supervision Targets in Financial Forecasting
RAMAC: Multimodal Risk-Aware Offline Reinforcement Learning and the Role of Behavior Regularization
Dynamics of neural scaling laws in random feature regression with powerlaw-distributed kernel eigenvalues
Position: AI Should Facilitate Democratic Deliberation at Scale
Position: Multi-Agent Systems Should Prioritize Concurrency Control
cMoLLM at Scale: Horizontal Scaling Laws for Convolutionally-Gated Mixture-of-LLMs
DeepAnalyze: Agentic Large Language Models for Autonomous Data Science
Position: From Crowdsourcing to Crowd-LLM-Sourcing and LLM-Sourcing
Efficient Stochastic Optimisation via Sequential Monte Carlo
NetDiff: Graph Diffusion with Improved Global Capabilities to Generate and Update Mobile Network Topologies
CSG: Cognitive Structure Generation for Intelligent Education
Dynamic Fractal Mamba: A Neural Renormalization Group Flow for Scale-Invariant Sequence Modeling
Scalable Simulation-Based Model Inference with Test-Time Complexity Control
Privileged Information Distillation for Language Models
Reuse your FLOPs: Scaling RL on Hard Problems by Conditioning on Very Off-Policy Prefixes
ProSAR: Prototype-Guided Semantic Augmentation and Refinement for Time Series Contrastive Learning
MedMosaic: A Challenging Large Scale Benchmark of Diverse Medical Audio
FusionCell: Cross-Attentive Fusion of Layout Geometry and Netlist Topology for Standard-Cell Performance Prediction
MetaBio: Learning from metadata for bioacoustics foundation models
A Machine-Learned Comorbidity Index
Structured Expert Routing with Multi-View Task Priors for Offline Meta-Reinforcement Learning
Towards On-Policy SFT: Distribution Discriminant Theory and its Applications in LLM Training
StructMAR: Structure-Aware Masked Autoregression for Explicit Layout Alignment in Text-to-Image Generation
Reward-free Alignment for Conflicting Objectives
Offline Reinforcement Learning with Universal Horizon Models
SPADA: A Verifiable Test-Driven Agent for Controllable Parametric CAD Assembly Generation
Offline Reinforcement Learning with Generative Trajectory Policies
Finite-time Convergence Analysis of Actor-Critic with Evolving Reward
Language Generation with Replay: A Learning-Theoretic View of Model Collapse
DR$^2$Seg: Decomposed Two-Stage Rollouts for Efficient Reasoning Segmentation in Multimodal Large Language Models
SLAE: Strictly Local All-atom Environment for Protein Representation
SVL: Empowering Spiking Neural Networks for Efficient 3D Open-World Understanding
Trajectory-Level Data Augmentation for Offline Reinforcement Learning
MentisOculi: Revealing the Limits of Reasoning with Mental Imagery
Olivia: Harmonizing Time Series Foundation Models with Power Spectral Density
Test-time Offline Reinforcement Learning on Goal-related Experience
Mosaic: Runtime-Efficient Multi-Agent Embodied Planning
Refined Analysis of Entropy-Regularized Actor-Critic
Compositional Transduction with Latent Analogies for Offline Goal-Conditioned Reinforcement Learning
Improving Zero-Shot Offline RL via Behavioral Task Sampling
VIPO: Value Function Inconsistency Penalized Offline Reinforcement Learning
Expected Returns and Policy Inconsistency-Aware Offline Federated Deep Reinforcement Learning
Continuous Diffusion Models Can Obey Formal Syntax
Turbo4DGen: Ultra-Fast Acceleration for 4D Generation
Bring My Cup! Personalizing Vision-Language-Action Models with Visual Attentive Prompting
Rethinking Forgery Attacks on Semantic Watermarks in Black-Box Settings: A Geometric Distortion Perspective
Offline Reinforcement Learning of High-Quality Behaviors Under Robust Style Alignment
Inference-time Alignment with Rewards in Besov Spaces: Provable Advantages of Feature Learning and Multi-Step Policy Updates
Action-Sufficient Goal Representations
Latent Diffusion Pretraining for Crystal Property Prediction
Evaluating Language Models in Realistic Conversational Contexts
Optimizing Return Distributions with Distributional Dynamic Programming
Latent Spherical Flow Policy for Reinforcement Learning with Combinatorial Actions
The Pareto-optimal Trade-off between Regret and Statistical Inference in Linear Stochastic Bandits under Safety Constraints
Taming the Aleatoric Impulse in Off-Policy Reinforcement Learning
CSPO: Constraint-Sensitive Policy Optimization for Safe Reinforcement Learning
Demystifying MaskGIT Sampler and Beyond: Adaptive Order Selection in Masked Diffusion
Return-Critic: Bridging Goal Discrepancy for Efficient Visual Reinforcement Learning
Multi-Head Attention as a Source of Catastrophic Forgetting in MoE Transformers
PAMD: Structured Adaptive Distances for Bisimulation Representations in Visual Reinforcement Learning
Harmonized Dual Policy Improvement for Model-based Reinforcement Learning
Geometry-Guided Generative Representation for Functional Brain Graphs
A Flat Vocabulary or a Rich Hierarchy? Re-introducing Intrinsic Structure Transforms the Autoregressive Image Generation
CoRe: Combined Rewards with Vision-Language Model Feedback for Preference-Aligned Reinforcement Learning
Efficient and Uncertainty-Aware Diffusion Framework for Offline-to-Online Reinforcement Learning
Discrete Tilt Matching
Sharp Inequalities between Total Variation and Hellinger Distances for Gaussian Mixtures
Inducing Overthink: Hierarchical Genetic Algorithm-based DoS Attack on Black-Box Reasoning Models
Uncertainty-Guided Exploration and Stable Planning for Sparse-Reward Manipulation from Limited Demonstrations
MIST: Moment-Aligned Invariant Stability Transform for Robust Flow Matching
Reward Under Attack: Analyzing the Robustness and Hackability of Process Reward Models
Direct Flow Q-Learning
Shift-Dependent Asymmetry: Orthogonal Inverse Low-Rank Adaptation for Federated Medical Segmentation
Scheduling Thoughts: Learning the Order of Thought in Diffusion Language Models
Learning Taxonomic Trees with Hierarchical Representation Regularization for Large Multimodal 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
Prioritized Model Experience Replay
GeoEvo: Identity-Aware Potential Game with Geometric Evolution for Personalized Multimodal Federated Learning
Stable Deep Reinforcement Learning via Isotropic Gaussian Representations
Coupled Cluster con MoLe: Molecular Orbital Learning for Neural Wavefunctions
Derivative Informed Learning of Exchange-Correlation Functionals
Revisiting Regularized Policy Optimization for Stable and Efficient Reinforcement Learning in Two-Player Games
Bioacoustic Geolocation: Species Sounds as Geographic Signals
What Makes Value Learning Efficient in Residual Reinforcement Learning?
Probabilistically-routed Bayesian Additive Spanning Trees for Learning on Constrained Domains
Multivariate distributional reinforcement learning using sliced divergences
Epistemic Gain, Aleatoric Cost: Uncertainty Decomposition in Multi-Agent Debate for Math Reasoning
Decision Transformers As Zero-Shot Learners via Text-Behavior Alignment
Agora: Toward Autonomous Bug Detection in Production-Level Consensus Protocols with LLM Agents
NonZero: Interaction-Guided Exploration for Multi-Agent Monte Carlo Tree Search
Robust Self-reflective Hashing for Cross-modal Retrieval with Noisy Label
Cycle-of-Science: Reliable Reasoning through Counterfactual Verification for Agent Decision Making
Distributionally Robust Markov Games with Average Reward
Recurrent Structural Policy Gradient for Partially Observable Mean Field Games
FOAM: Blocked State Folding for Memory-Efficient LLM Training
Feed-Forward Taylor-Gaussians-Flow: Towards Non-uniform Motion for Novel View Synthesis from Monocular Video
Discovering Implicit Large Language Model Alignment Objectives
MCCE: A Framework for Multi-LLM Collaborative Search in Discrete Spaces with Similarity-Filtered Preference Learning
Learning Disentangled Multi-Agent World Model for Decentralized Control
GTPO and GRPO-S: Token and Sequence-Level Reward Shaping with Policy Entropy
SimpleMem: Efficient Lifelong Memory for LLM Agents
Agent0-VL: Exploring Self-Evolving Agent for Tool-Integrated Vision-Language Reasoning
Hybrid Reinforcement Learning in Adversarial Markov Decision Processes
Learning Tight Rejection Boundaries without Negatives for Strict One-Class Audio Deepfake Detection
Structure-Induced Information for Rerooting Levin Tree Search
TUR-DPO: Topology- and Uncertainty-Aware Direct Preference Optimization
Joint-Space Empowerment as a Theory of Dexterous Motor Coordination
Revealing Long-context Potential of Attention Heads via Frequency Kernels
Certifying Graph Neural Networks Against Label and Structure Poisoning
Mixture of Horizons in Action Chunking
Phase-Aware Mixture of Experts for Agentic Reinforcement Learning
Benchmarking Reward Hack Detection in Code Environments via Contrastive Analysis
UniSVQ: 2-bit Unified Scalar-Vector Quantization
Learning Interpretable Options by Identifying Reward Diffusion Bottlenecks in Reinforcement Learning
Position: Want Better ML Reviews? Stop Asking Nicely and Start Incentivizing with a Credit System
FreeRet: MLLMs as Training-Free Retrievers
De4D-SLAM: Gradient-Isolated Static-Dynamic Decoupling for Monocular SLAM in Dynamic Environments
Beyond Attention Imbalance: Mitigating Hallucinations via Spectral Surgery
Bullet Trains: Parallelizing Training of Temporally Precise Spiking Neural Networks
GenShield: Unified Detection and Artifact Correction for AI-Generated Images
Posterior Concentration of Physics-Informed Neural Networks for Elliptic PDEs
DeFacto: Counterfactual Thinking with Images for Enforcing Evidence-Grounded and Faithful Reasoning
The Relative Instability of Model Comparison with Cross-validation
Rh-3DGS: Robust Open-Vocabulary Scene Understanding via Riemannian Huber Distillation and Manifold-Aware Sampling
Scaling Multi-Agent Environment Co-Design with Diffusion Models
When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems
Towards Theoretical Understanding of Transformer Test-Time Computing: Investigation on In-Context Linear Regression
Reasoning Can Be Restored by Correcting a Few Decision Tokens
Action Manifold Smoothing: A Lipschitz Pathway Perspective on High-Dimensional Reinforcement Learning
Golden Goose: A Simple Trick to Synthesize Unlimited RLVR Tasks from Unverifiable Internet Text
Detecting and Filtering Unsafe Training Data via Data Attribution with Denoised Representation
Rethinking Federated Prompt Learning for Medical Images: From Textual Tuning to Visual Manifold Anchoring
NITP: Next Implicit Token Prediction for LLM Pre-training
Learning Gaussian Graphical Models from a Glauber Trajectory Without Mixing
HIAL: Towards Semantics-Aware Hypergraph Active Learning via Dual-Perspective Information Maximization
Spectral Flow Matching: Stabilizing Stochastic GFlowNets via Frequency-Domain Regularization
Accuracy and Normalized Accuracy under Length Bias: Analysis, Guidelines, and a Bayesian Alternative
Context Tuning for In-Context Optimization
Weight-sparse transformers have interpretable circuits
Multi-Label Test-Time Adaptation with Bayesian Conditional Priors
LightAVSeg: Lightweight Audio-Visual Segmentation
ScaleErasure: Inference-Time Minimal Intervention for Precise Concept Erasure in Next-Scale Autoregressive Image Generation
CIRBench: Evaluating Large Language Models as LLVM IR Optimizers
Online Continual Learning with Dynamic Label Hierarchies
WestWorld: A Knowledge-Encoded Scalable Trajectory World Model for Diverse Robotic Systems
SPR: A Structured Prompt Refinement Network for Modality Missing
Position: Weight Space Should Be a First-Class Generative AI Modality
Monotonic Variational Gaussian Process for Efficient Data Collection
Optimal Regret for Policy Optimization in Contextual Bandits
RAG without Forgetting: Continual Query-Infused Key Memory
DRIVE: Best Data Scheduling Practices for Reinforcement Learning with Verifiable Reward in Competitive Code Generation
FedPissa: Towards Federated Personalized Adaptation of Foundation Models via LoRA Subspace Mapping
Reasoning-VLA: An Efficient and Spatial-Guided General Vision-Language-Action Reasoning Model for Autonomous Driving
Uncovering Latent Communication Patterns in Brain Networks via Adaptive Flow Routing
Distributed Direct Preference Optimization
*MemPot*: Defend Against Memory Extraction Attack with Optimized Honeypots
Riemannian Dueling Optimization
Axiomatic Atlas: A Prescriptive Framework for Neural Architecture Design
Difference-Aware Decision Learning for Multimodal Image Fusion
MACD: Model-Aware Contrastive Decoding via Counterfactual Data for Video-LLMs
Scalable Option Learning in High-Throughput Environments
FuseFSS: Efficient Secure LLM Inference with Function Secret Sharing
EvReflection: Event-Driven Micro-Dynamics for Reflection Removal
SubspacePath Pruner: Inference-time Pruning via Probe-based Representation–Parameter Coupling
Beyond Instance-Level Self-Supervision in 3D Multi-Modal Medical Imaging
API: Adaptive Prototype Imputation for Incomplete Multimodal Sentiment Analysis
Identifying and Mitigating Errors in Gradient Aggregation of Distributed Data Parallel Training
3D-RFT: Reinforcement Fine-Tuning for Video-based 3D Scene Understanding
XDomainBench: Diagnosing Reasoning Collapse in High-Dimensional Scientific Knowledge Composition
TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization
FLAC: Maximum Entropy RL via Kinetic Energy Regularized Bridge Matching
On the Effect of Misspecifying the Embedding Dimension in Low-rank Network Models
EAKV: An Entropy-Driven Adaptive KV Compression Framework for Long Video Understanding
Toward Subspace-Perturbed Trajectory-Aware Backdoor Attacks in Deep Reinforcement Learning
DGG-HMR: Multi-Person Human Mesh Recovery with Depth-Guided Geometric Anchoring
Visual Para-Thinker: Divide-and-Conquer Reasoning for Visual Comprehension
Open-o3-Video: Grounded Video Reasoning with Explicit Spatio-Temporal Evidence
DyCon: Dynamic Reasoning Control via Evolving Difficulty Modeling
CPMöbius: Iterative Coach–Player Reasoning for Data-Free Reinforcement Learning
Deep networks learn to parse uniform-depth context-free languages from local statistics
The Geometry of Reasoning: Self-Evaluation via Layerwise Trajectory Evolution
Deep Single-Index Fréchet Regression
Leak@$k$: Unlearning Does Not Make LLMs Forget Under Probabilistic Decoding
Fast-SAM3D: 3Dfy Anything in Images but Faster
CURE: Context-driven Diffusion with Progressive Expansion for Single Domain Generalization in Time Series Classification
Adaptive Personalized Federated Learning via Multi-task Averaging of Kernel Mean Embeddings
Concept-Guided Tokenization: Closing the Gap Between Reconstruction and Generation
MedREK: Retrieval-Based Editing for Medical LLMs with Key-Aware Prompts
Domain-Shift-Aware Conformal Prediction for Large Language Models
Focusing: View-Consistent Sparse Voxels for Efficient 3D VAE
Metric–-Phase Fields: Decoupling Distance and Sign for Thin-Structure Reconstruction from Unoriented Point Clouds
Position: Solipsistic superintelligence is unlikely to be cooperative
Trustworthy Federated Label Distribution Learning under Annotation Quality Disparity
Scaling Unsupervised Multi-Source Federated Domain Adaptation through Group-Wise Discrepancy Minimization
Beyond Binary: Continuous State Optimization with Graph-Structured Objectives
$\tau$-Voice: Benchmarking Full-Duplex Voice Agents on Real-World Domains
A Theoretical Framework for Statistical Evaluability of Generative Models
Position: Medical AI Neglects Real Treatment Outcomes
Learnability-Driven Knowledge Assimilation for Class-Incremental Semantic Segmentation
EchoRL: Reinforcement Learning via Rollout Echoing
Realizable Bayes-Consistency for General Metric Losses
High-accuracy sampling for diffusion models and log-concave distributions
A Refined Generalization Analysis for Extreme Multi-class Supervised Contrastive Representation Learning
Iterative Refinement Neural Operators are Learned Fixed-Point Solvers: A Principled Approach to Spectral Bias Mitigation
Provably Data-driven Multiple Hyper-parameter Tuning with Structured Loss Function
Structure-aware Granular-Ball based Information Bottleneck for Multi-modal Clustering
Efficient Multi-Agent Reasoning via Confidence-Guided Adaptive Debate
Experience-Evolving Multi-Turn Tool-Use Agent with Hybrid Episodic–Procedural Memory
The Implicit Bias of Steepest Descent with Mini-batch Stochastic Gradient
Moment Matching Q-Learning
Harmful Overfitting in Sobolev Spaces
LAMP: Data-Efficient Linear Affine Weight-Space Models for Parameter-Controlled 3D Shape Generation and Extrapolation
Required Spine Optional Limbs: Heterogeneous Federated Learning via Backbone-sharing and Activation-guided Selection
SpikeCLR: Self-Supervised Contrastive Learning for Visual Representations with Spiking Neural Networks
Just-In-Time Reinforcement Learning: Continual Learning in LLM Agents Without Gradient Updates
Feature Bagging Provides Stability
General and Efficient Steering of Unconditional Diffusion Models
High-Dimensional Learning Dynamics of Quantized Models with Straight-Through Estimator
Negative Sampling From the Ground Up: A Redesign for Graph-based Recommendations
FedHera: Towards Drift-Resilient Federated Fine-tuning with Heterogeneous Resources
Boosting Monocular Metric Depth Estimation via Bokeh Rendering
Advancing SVD-based LLM Compression via Layer-Wise Error Model Search
Mitigating Gradient Pathology in PINNs through Aligned Constraint
Depth-Progressive Monotonic Learning without Backpropagation
Understanding Generalization from Embedding Dimension and Distributional Convergence
OmniDenseCap: Scripting Multi-Scene Videos with Time-Aware and Structural Audio-Visual Captions
Tight Stability Bounds for Robust Distributed Learning: Byzantine Failures Hurt Generalization More than Data Poisoning
Coverage Improvement and Fast Convergence of On-policy Preference Learning
Furina: Fragmented Uncertainty-Driven Refusal Instability Attack
SkillTrojan: Backdoor Attacks on Skill-Based Agent Systems
Learning to Explore: Scaling Agentic Reasoning via Exploration-Aware Policy Optimization
U$^3$CF: Unbiased, Unconfounding, and Unified Causal Framework for Multi-Target Domain Adaptation
OMAC: A Holistic Optimization Framework for LLM-Based Multi-Agent Collaboration
Beyond Euclidean Clipping: Overcoming Exploration Collapse in LLM RL via Riemannian Isometric Policy Optimization
On the Sharp Input-Output Analysis of Nonlinear Systems under Adversarial Attacks
Parsimonious Learning-Augmented Online Metric Matching
The Flexibility Trap: Rethinking the Value of Arbitrary Order in Diffusion Language Models
Prediction-Powered Risk Monitoring of Deployed Models for Detecting Harmful Distribution Shifts
RLCracker: Evaluating the Worst-Case Vulnerability of LLM Watermarks with Adaptive RL Attacks
Position: Peer Review Should Be Calibrated via LLM Scoring
How to Price Data: A Market Equilibrium Based Approach
Weights to Code: Extracting Interpretable Algorithms from the Discrete Transformer
DeepImageSearch: Benchmarking Multimodal Agents for Context-Aware Image Retrieval in Visual Histories
Position: Causality is Key for Interpretability Claims to Generalise
Uncovering Bias Mechanisms in Observational Studies
Off-Policy Evaluation Beyond Overlap under Network Interference
SegPVSG: Panoptic Video Scene Graph Generation via Temporal Focusing and Generative Augmentation
Conditional Distributional Treatment Effects: Doubly Robust Estimation and Testing
REST: Diffusion-based Real-time End-to-end Streaming Talking Head Generation via ID-Context Caching and Asynchronous Streaming Distillation
FOCUS: DLLMs Know How to Tame Their Compute Bound
Budgeted Active Experimentation for Treatment Effect Estimation from Observational and Randomized Data
OptMaster: A DAG-Based Framework for Formulation and Heuristic Discovery in Optimization
VidLaDA: Bidirectional Diffusion Large Language Models for Efficient Video Understanding
DISCO: Mitigating Bias in Deep Learning with Conditional Distance Correlation
Relational Structural Causal Models
Prism: Spectral-Aware Block-Sparse Attention
Sparser Block-Sparse Attention via Token Permutation
How RLHF Amplifies Sycophancy
GENEB: Why Genomic Models Are Hard to Compare
SPATIA: Multimodal Generation and Prediction of Spatial Cell Phenotypes
Doubly Robust Distributionally Robust Offline Contextual Pricing
Distilling Geometry Priors for 3D-Consistent Video Generation
Meta Context Engineering via Agentic Skill Evolution
Modeling Covariate Transition for Efficient Estimation of Longitudinal Treatment Effects in Randomized Experiments
CyberJurors: A Multi-Agent Simulation Task for E-Commerce Disputes Verdict
Toward Scalable and Valid Conditional Independence Testing with Spectral Representations
Zeroth-Order Forward-Only SNN Training Inspiring Neuromorphic On-Chip Learning
Federated Causal Inference on Multi-Site Observational Data via Propensity Score Aggregation
Multi-View Causal Discovery without Non-Gaussianity: Identifiability and Algorithms
Fast and Expressive Multi-Byte Prediction with Probabilistic Circuits
Position: World Models as an Intermediary between Agents and the Real World
Prefix cache aware data reordering for LLM augmented database analytics
Convex Dataset Valuation for Post-Training
Treatment Responder Classification with Abstention
SpecForge: A Flexible and Efficient Open-Source Training Framework for Speculative Decoding
Efficient Bayesian Inference from Noisy Pairwise Comparisons
Evaluating LLMs When They Do Not Know the Answer: Statistical Evaluation of Mathematical Reasoning via Comparative Signals
HALO: A Unified Vision-Language-Action Model for Embodied Multimodal Chain-of-Thought Reasoning
Symbal: Detecting Systematic Misalignments in Model-Generated Captions
AutoMat: Physics-Guided Agentic Reasoning for Solving Ill-Posed Inverse Microscopy Problems
AlphaGRPO: Unlocking Self-Reflective Multimodal Generation in Unified Multimodal Models via Decompositional Verifiable Reward
VenusBench-Mobile: A Challenging and User-Centric Benchmark for Mobile GUI Agents with Capability Diagnostics
Gated Relational Alignment via Confidence-based Distillation for Efficient VLMs
Bridging the Gap Between Average and Discounted TD Learning
EvoC2F: Compiling Tool Orchestration for Efficient and Evolvable LLM Agents
Benchmarking and Evolving Reason-Reflect-Rectify for Reflective Visual Generation
Don't Overthink with Pixels: Efficient Reasoning for Segmentation
Not All Prefills Are Equal: PPD Disaggregation for Multi-turn LLM Serving
Towards One-to-Many Temporal Grounding
The Geometry of Narrow Fine-Tuning Degradation: Trajectory Lock-in and Spectral Bifurcation
DuetServe: Harmonizing Prefill and Decode for LLM Serving via Adaptive GPU Multiplexing
Even Faster Kernel Matrix Linear Algebra via Density Estimation
Threshold-Guided Optimization for Visual Generative Models
Regularized Offline Policy Optimization with Posterior Hybrid Bayesian Belief
Efficient Test-Time Scaling via Hierarchical Search and Self-Verification for Discrete Diffusion 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
Optimal Estimation of Continuous Treatment Effects with Kernel Ridge Regression
Enhanced Latent-Space Adversarial Training for Super-Resolution
GAM-RAG: Gain-Adaptive Memory for Evolving Retrieval in Retrieval-Augmented Generation
Networked Information Aggregation for Binary Classification
Risk-Bounded Distribution Reconstruction: Stable Statistic Calibration for Long-Tailed Recognition
TCAP: Tri-Component Attention Profiling for Unsupervised Backdoor Detection in MLLM Fine-Tuning
Rewiring Experts on the Fly: Continuous Rerouting for Better Online Adaptation in Mixture-of-Expert models
MAGIC: A Co-Evolving Attacker–Defender Adversarial Game for Robust LLM Safety
Revisiting the Platonic Representation Hypothesis: An Aristotelian View
PACER: Acyclic Causal Discovery from Large-scale Interventional Data
Disentangling Intent from Role: Adversarial Self-Play for Persona-Invariant Safety Alignment
Position: Agentic AI systems should be making Bayes-consistent decisions
Can Simple Denoising Improve Uniform State Diffusion Models?
Adaptive Code Watermarking Through Reinforcement Learning
Graph is a Natural Regularization: Revisiting Vector Quantization for Graph Representation Learning
Efficient Learning of Deep State Space Models via Importance Smoothing
Hierarchical Multi Scale Graph Neural Networks: Scalable Heterophilous Learning with Oversmoothing and Oversquashing Mitigation
OSAQ: Outlier Self-Absorption for Accurate Low-bit LLM Quantization
TGPO: Efficient Policy Optimization through Sequence Anchor and Information Gating
A Bi-metric Framework for Efficient Nearest Neighbor Search
On the Anisotropy of Score-Based Generative Models
FocalPolicy: Frequency-Optimized Chunking and Locally Anchored Flow Matching for Coherent Visuomotor Policy
VideoTrace-R1: Long Video-based Retrieval-Augmented Generation via Temporal Path Graph Understanding
Discrete Survival Knowledge Distillation for Competing Risks Analysis
GKD-Recruiter: Jointly Modeling Social and Task Heterogeneity for Spatial Crowdsourcing via Graph Knowledge Distillation
Do LLMs “Feel”? Emotion Circuits Discovery and Control
MuLoCo: Muon is a Practical Inner Optimizer for DiLoCo
Learning High-Dimensional Parity Functions with Product Networks using Gradient Descent
Logit Distance Bounds Representational Similarity
Local MAP Sampling for Diffusion Models
SURGE:Unbiased Data Assimilation for Diffusion Model via Particle Filtering
From Parameters to Feature Space: Task Arithmetic for Backdoor Mitigation in Model Merging
Tractable Expected Information Gains for Exponential Family Posteriors
Bayesian model selection and misspecification testing in imaging inverse problems only from noisy and partial measurements
PerceptionRubrics: Calibrating Multimodal Evaluation to Human Perception
Tokenised Flow Matching for Hierarchical Simulation Based Inference
Richer Bayesian Last Layers with Subsampled NTK Features
StreamFlow: Theory, Algorithm, and Implementation for High-Efficiency Rectified Flow Generation
Bridging RGB and RAW: Single-step Deterministic Flow with Homogeneous Aligned Guidance
Learning Multi-Agent Coordination via Sheaf-ADMM
TabMGP: Martingale Posterior with TabPFN
Budget-Constrained Step-Leve Diffusion Caching
ReSeek: A Self-Correcting Framework for Search Agents with Instructive Rewards
CAPTCHA Solving for Native GUI Agents: Automated Reasoning-Action Data Generation and Self-Corrective Training
HONet: Data-Efficient Learning for Exact Cover Problems via Hypergraph Optimization
Attentive Multi-Layer Fusion for Vision Transformers
Tailoring Strictly Proper Scoring Rules for Downstream Tasks: An Application to Causal Inference
HexGen-3: A Fully Disaggregated LLM Serving Framework with Fine-Grained Heterogeneous Resource Autoscaling
TetraJet-v2: Accurate NVFP4 Training for Large Language Models with Oscillation Suppression and Outlier Control
OmniFit: Bridging Modalities via Layer-Adaptive Token Compression for Omnimodal Large Language Models
TabPack: Efficient Hyperparameter Ensembles for Tabular Deep Learning
When Does Sparsity Mitigate the Curse of Depth in LLMs
Mitigating Reward Hacking in RLHF via Bayesian Non-negative Reward Modeling
Diffusion posterior sampling for simulation-based inference in tall data settings
Simultaneous Confidence Bounds for Aggregated Effects via Exact Subset Optimization
Generalizable and Composable Multi-Model Embedding Translation
Mechanistic Interpretability as Statistical Estimation: A Variance Analysis
Uncovering Grounding IDs: How External Cues Shape Multi-Modal Binding
DC-LA: Difference-of-Convex Langevin Algorithm
Platonic Transformers: A Solid Choice For Equivariance
Vector Linking via Cross-Model Local Isometric Consistency
A Recursive Decomposition Framework for Causal Structure Learning in the Presence of Latent Variables
Anti-Aliasing Matters: A Dynamic Network for Time Series Forecasting
On the Power of Statistics in Class-Incremental Learning with Pretrained Models
When Does Adaptation Win? Scaling Laws for Meta-Learning in Quantum Control
CARE: Adaptive Calibration for Reliable Recommendations
Don't Force the Fit: Bounded Log-Likelihood Loss for Enhanced Reasoning in Large Language Models
CORAL: Uncertainty-Aware Regulation of Exposure Concentration in Recommender Systems
ETS: Energy-Guided Test-Time Scaling for Training-Free RL Alignment
Accelerating Langevin Monte Carlo via Efficient Stochastic Runge-Kutta Methods beyond Log-Concavity
A Capacity-Based Rationale for Multi-Head Attention
The Differences Between Direct Alignment Algorithms are a Blur
Zooming without Zooming: Region-to-Image Distillation for Fine-Grained Multimodal Perception
Mitigating Premature Exploitation in Particle-based Monte Carlo for Inference-Time Scaling
Scalable Power Sampling: Unlocking Efficient, Training-Free Reasoning for LLMs via Distribution Sharpening
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
Position: Unplugging a Seemingly Sentient Machine Is the Rational Choice — A Metaphysical Perspective
Column Thresholding for Sparse Spiked Wigner Models: Improved Signal Strength Requirements
Optimal Quantum Speedups for Repeatedly Nested Expectation Estimation
LabBuilder: Protocol-Grounded 3D Layout Generation for Interactable and Safe Laboratory
Beyond Euclidean Summaries: Online Change Point Detection for Distribution-Valued Data
Markov Chain Monte Carlo without Evaluating the Target: an Auxiliary Variable Approach
Stationary MMD Points
Doc-to-LoRA: Learning to Instantly Internalize Contexts
Fingerprinting Pre-trained Encoders under Arbitrary Downstream Fine-Tuning via Adversarial Shifting
Coarse-Grained Boltzmann Generators
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
SPUR: Scale-Partitioned Uncertainty Rectification for Robust UAV-on-UAV Interception
Neural Low-Discrepancy Sequences
Coupled Training with Privileged Features and Unlabeled Data
FlowCloud: Learning Continuous Spatiotemporal Dynamics from Unpaired Sparse Point Cloud Snapshots
Disentangling Latent Risk Pathways via Bayesian Hypergraph Inference
Spectral-Informed Neural Networks Outperform Spectral methods in High-dimensional PDEs
Colorful Pinball: Density-Weighted Quantile Regression for Conditional Guarantee of Conformal Prediction
Cross-Modal Semantic Decoupling and Transfer for Text-to-Visible-Infrared Person Re-Identification
Probabilistic Modeling of Latent Agentic Substructures in Deep Neural Networks
Rethinking the Flow-based Gradual Domain Adaption: A Semi-Dual Optimal Transport Perspective
SSR-Merge: Subspace Signal Routing for Training-Free LoRA Merging in Diffusion Models
SCORE: A Unified Framework for Overshoot Refund in Online FDR Control
Accurate Large-scale Uncertainty Quantification using Stochastic Gradient Markov Chain Monte Carlo
X-EviProbe: Post-hoc Parameter-free Evidential Uncertainty Quantification for Frozen Graph Neural Networks
Time series saliency maps: Explaining models across multiple domains
Is Data Shapley Not Better than Random in Data Selection? Ask NASH
CacheEdit: Efficient Multi-round Image Editing via Adaptive Token-wise Reuse.
Unsupervised Disentanglement Without Compromises : How Functional Orthogonality Enforces Identifiability
Retro-Expert: Collaborative Reasoning for Interpretable Retrosynthesis
Adapting Noise to Data: Generative Flows from Learned 1D Processes
Measuring Meta-Cultural Competency: A Spectral Framework for LLM Knowledge Structures
In-Training Defenses Against Emergent Misalignment in Language Models
Draft-Conditioned Constrained Decoding for Structured Generation in LLMs
Same Question, Different Lies: Cross-Context Consistency (C³) for Black-Box Sandbagging Detection
Margin-Adaptive Confidence Ranking for Reliable LLM Judgement
TokenDrop: Token-Level Importance-Aware Backward Propagation Skipping for Efficient LLM Fine-Tuning
Multi-Agent Reinforcement Learning with Submodular Reward
POET-X: Memory-efficient LLM Training by Scaling Orthogonal Transformation
T-measure: A Topology-Consistent Metric for Binary Segmentation
Consistency Training Is Not Neutral to Alignment
Optimal Domain-Aware Privacy Mechanisms for Synthetic Data Generation
UI2Code^N: UI-to-Code Generation as Interactive Visual Optimization
Catch-22: On the Fundamental Tradeoff Between Detectability and Robustness in LLM Watermarking
Robust Strategic Classification under Decision-Dependent Cost Uncertainty
Quantifying LLM Attention-Head Stability: Implications for Circuit Universality
Contrastive Spectral Rectification: Test-Time Defense towards Zero-shot Adversarial Robustness of CLIP
Constrained hybrid modelling to predict microbial dynamics and organic matter turnover in soil systems
A New Framework for Cybersecurity Refusals in AI Agents
Multilingual Safety Alignment Via Sparse Weight Editing
Order within Chaos: Capturing Intrinsic Energy Anomalies for AI-Manipulated Image Forgery Localization
Training Language Model Agents to Find Vulnerabilities with CTF-Dojo
Position: To Defend Against Cyber Attacks, We Must Teach AI Agents to Hack
Spurious Rewards: Rethinking Training Signals in RLVR
TDM-R1: Reinforcing Few-Step Diffusion Models with Non-Differentiable Reward
Towards Context-Invariant Safety Alignment for Large Language Models
CoT is Not the Chain of Truth: An Empirical Internal Analysis of Reasoning LLMs for Fake News Generation
SafeHarbor: Defining Precise Decision Boundaries via Hierarchical Memory-Augmented Guardrail for LLM Agent Safety
Distributional Active Inference
Position: Mechanisms for Aggregated Individual Reporting Should be Established for Post-Deployment Evaluation
CAT-Q: Cost-efficient and Accurate Ternary Quantization for LLMs
DisPPO: Quantile-Based Distributional Reinforcement Learning for Large Language Models
Adversarially Robust Approximate Furthest Neighbor
LLM Self-Recognition: Steering and Retrieving Activation Signatures
Controlled SDEs for Long-Horizon Motion Generation under Latent Decision Uncertainty
Slash the Sink: Sharpening Structural Attention Inside LLMs
Search for Truth from Reasoning: A Dynamic Representation Editing Framework for Steering LLM Trajectories
Uncovering the Gradient Geometry of Long CoT: A Spectral-guided Approach to Reasoning Distillation
Rational Transductors
TVI-CoT: Text-Visual Interleaved Chain-of-Thought Reasoning for Multimodal Understanding
SPARD: Defending Harmful Fine-Tuning Attack via Safety Projection with Relevance–Diversity Data Selection
OpenIKLR: Bridging the Reasoning Gap in Open-World Scenarios via Iterative Premise Completion
G2D2: Gradient-Guided Discrete Diffusion for Inverse Problem Solving
Dense associative memory for Gaussian distributions
Fine-Tuning Masked Diffusion for Provable Self-Correction
Rethinking the Design Space of Reinforcement Learning for Diffusion Models: On the Importance of Likelihood Estimation Beyond Loss Design
MetaMoE: Diversity-Aware Proxy Selection for Privacy-Preserving Mixture-of-Experts Unification
Elastic Diffusion Transformer
Olaf-World: Orienting Latent Actions for Video World Modeling
Efficient Diffusion Models under Nonconvex Equality and Inequality constraints via Landing
Any2Any: Unified Arbitrary Modality Translation for Remote Sensing
Rotary Position Encodings for Graphs
Reasoning on the Manifold: Bidirectional Consistency for Self-Verification in Diffusion Language Models
Implicit Action Chunking for Smooth Continuous Control
When Sample Selection Bias Precipitates Model Collapse
PULSE: Generative Phase Evolution for Non-Stationary Time Series Forecasting
Taming the Recent-Data Bias: Towards Robust Time Series Forecasting with Global Context
RA-VLA: Retrieval-Augmented VLA for Test-Time Adaptation
Text Generation as Continuous Latent Dynamics via Reinforcement Learning
Plug-and-Play Guidance for Discrete Diffusion Models via Gradient-Informed Logit Correction
Measurement-Consistent Langevin Corrector for Stabilizing Latent Diffusion Inverse Problem Solvers
Just Y-Prediction: Enabling Historical Cumulative Inconsistency in Label Diffusion for Learning with Noisy Label
Beyond Generative Priors: Minority Sampling with JEPA-Guided Diffusion
Orthogonal Model Merging
Self-Guidance: Enhancing Neural Codecs via Decoder Manifold Alignment
Where Rectified Flows Leak: Characterizing Membership Signals Along the Interpolation Path
Information-Geometric Adaptive Sampling for Graph Diffusion
Suppress and Diversify: Refining Robust Pathways for Corruption Robustness
IDLM: Inverse-distilled Diffusion Language Models
Categorical Flow Maps
Insertion Based Sequence Generation with Learnable Order Dynamics
Are First-Order Diffusion Samplers Really Slower? A Fast Forward-Value Approach
AlphaRouter: Token-level Routing Between SLM and LLM with Reinforcement Learning and Tree Search
Data Provenance Auditing of Fine-Tuned Large Language Models with a Text-Preserving Technique
Effective Reasoning Chains Reduce Intrinsic Dimensionality
Cascaded Flow Matching for Heterogeneous Tabular Data with Mixed-Type Features
Riemannian Diffusion Models on General Manifolds via Physics-Informed Neural Networks
Weaving Graph over Tokens: Contextualizing Structured Sequences for LLMs
Particle-Guided Diffusion Models for Partial Differential Equations
HGMem: Hypergraph-based Working Memory to Improve Multi-step RAG for Long-Context Complex Relational Modeling
Mitigating the Contractivity Trap in Diffusion ODEs via Stein Stabilization
Initialization is Half the Battle: Generating Diverse Images from a Guidance Potential Posterior
SINQ: Sinkhorn-Normalized Quantization for Calibration-Free Low-Precision LLM Weights
Condition-Aware Graph Flow Matching for Modeling the Distributions of Complex Physical Systems
Position: The Systemic Lack of Agency in Visual Reasoning
Attacks on Machine-Text Detectors Retain Stylistic Fingerprints
Sequential Kernel-based Conditional Independence Testing via Adaptive Betting
DTKG: Dual-Track Knowledge Graph-Verified Reasoning Framework for Multi-Hop QA
One-shot Entropy Minimization for Language Model Reasoning
Active Learning with Foundation Model Priors: Efficient Learning under Class Imbalance
GAAVI: Global Asymptotic Anytime Valid Inference for the Conditional Mean Function
INT vs. FP: A Comprehensive Study of Fine-Grained Low-bit Quantization Formats
Language Generation in the Limit: Complexity Barriers and Implications for Learning
RelayCaching: Accelerating LLM Collaboration via Decoding KV Cache Reuse
AutoSizer: Automatic Sizing of Analog and Mixed-Signal Circuits via Large Language Model (LLM) Agents
Heterogeneous Customizable Personalized Federated Fine-Tuning Approach for Large Language Models
PRIM：Cooperative Dynamic Token Compression for Efficient Large Multimodal Models
Path-dependent Discrete Amortized Inference
VeRO: An Evaluation Harness for Agents to Optimize Agents
Ekka: Automated Diagnosis of Silent Errors in LLM Inference
Decoupling Reasoning and Confidence: Resurrecting Calibration in Reinforcement Learning from Verifiable Rewards
MechVQA: Benchmarking and Enhancing Multimodal LLMs on Comprehensive Mechanical Drawing Understanding
AAD-1: Asymmetric Adversarial Distillation for One-Step Autoregressive Video Generation
Toward Cybersecurity-Expert Small Language Models
How Reasoning Evolves from Post-Training Data: An Empirical Study Using Chess
AgentConductor: Topology Evolution for Multi-Agent Competition-Level Code Generation
Beyond Sunk Costs: Boosting LLM Pre-training Efficiency via Orthogonal Growth of Mixture-of-Experts
On the Identifiability of Poisson Branching Structural Causal Model Under Latent Confounding
VisualScore: Learning Holistic Visual Quality Scores via Multi-Task Reasoning
SAD-Flower: Flow Matching for Safe, Admissible, and Dynamically Consistent Planning
Implicit Preference Alignment for Human Image Animation
Thinking in Latent Space: Progressive Multimodal Simplification for Visual Reasoning
GEMQ: Global Expert-Level Mixed-Precision Quantization for MoE LLMs
InfoPO: Information-Driven Policy Optimization for User-Centric Agents
Uncovering Hidden Triggers: Backdoor Attribution in Language Models
Tailoring the Training: Difficulty-Aware Learning Strategy Allocation for Large Language Models
Fourier Features Let Agents Learn High Precision Policies with Imitation Learning
Robust Bayesian Optimisation with Unbounded Corruptions
AGZO: Activation-Guided Zeroth-Order Optimization for LLM Fine-Tuning
Controllable and explainable personality sliders for LLMs at inference time
AutoMS: Multi-Agent Evolutionary Search for Cross-Physics Inverse Microstructure Design
Rays as Pixels: Learning A Joint Distribution of Video and Camera Trajectories
InteractComp: Evaluating Search Agents With Ambiguous Queries
Do Vision and Text Cues Exhibit Evidential Coupling? UFO: A Benchmark for Compositional Multimodal Reasoning in Unified Models
A KL-regularization framework for learning to plan with adaptive priors
Weight Decay Improves Language Model Plasticity
Building Better Deception Probes Using Targeted Instruction Pairs
Learning to Emulate Chaos: Adversarial Optimal Transport Regularization
SiameseNorm: Breaking the Barrier to Reconciling Pre/Post-Norm
Frequency-Aware Perceptual Optimization for Low-Complexity Implicit Image Compression
Future Dynamic 3D Reconstruction: A 3D World Model with Disentangled Ego-Motion
Why Linear Recurrent Memory Works in Partially Observable Reinforcement Learning
V-ABS: Action-Observer Driven Beam Search for Dynamic Visual Reasoning
Can Large Language Models Generalize Procedures Across Representations?
Efficient-DLM: From Autoregressive to Diffusion Language Models, and Beyond in Speed
BubbleSpec: Turning Long-Tail Bubbles into Speculative Rollout Drafts for Synchronous Reinforcement Learning
DAVE: Distribution-aware Attribution via ViT Gradient Decomposition
MergeMix: Optimizing Mid-Training Data Mixtures via Learnable Model Merging
EasyBalance: Cross-Layer Load Balancing in Distributed MoE Inference
VectorWorld: Efficient Streaming World Model via Diffusion Flow on Vector Graphs
Faster Query-Key Learning Sharpens Attention in Self-Attention Models
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
The Geometry of Projection Heads: Conditioning, Invariance, and Collapse
A Fast and Soft Pattern Matcher for Trillion-Scale Corpus
When Simple Problems Wear Complex Costumes: Improving Efficiency in LRM’s Adaptive Reasoning
Graph Alignment via Dual-Pass Spectral Encoding and Latent Space Communication
The Cost of Information: Phase Transitions in Contextual Bandits with Paid Observations
Strategy Executability in Mathematical Reasoning: Leveraging Human–Model Differences for Effective Guidance
Olmix: A Framework for Data Mixing Throughout LM Development
The Cost of Learning under Multiple Change Points
Physics-Informed Residual Flows
gp2Scale: A Class of Compactly Supported Non-Stationary Kernels and Distributed Computing for Exact Gaussian Processes on 10 Million Data Points
RetrOrchestrator: A Multi-Step Retrosynthesis Agent Dynamically Orchestrating Single-Step Transition Models
Forget to Know, Remember to Use: Context-Aware Unlearning for Large Language Models
ProcMEM: Learning Reusable Procedural Memory from Experience via Non-Parametric PPO for LLM Agents
NanoFLUX: Distillation-Driven Compression of Large Text-to-Image Generation Models for Mobile Devices
PointCHR: Point Cloud Analysis via Curvature-Aware Hyperbolic Rectification
Learn to Think: Improving Multimodal Reasoning through Vision-Aware Self-Improvement Training
Heterogeneity-Aware Knowledge Sharing for Graph Federated Learning
Depth over Fidelity in Fixed-Budget Noisy Evolution Strategies
GoodDiffusion: Proactive Copyright Protection for Diffusion Generative Models via Learnable Sample-specific Signatures
RE-TRAC: REcursive TRAjectory Compression for Deep Search Agents
Utility Boundary of Dataset Distillation: Scaling and Coverage Laws
ArcDAE: Asymmetric Rectified Contrastive Diffusion Autoencoder for Unified Representation Learning
WarmServe: Enabling One-for-Many GPU Prewarming for Multi-LLM Serving
DualTimesField: Rethinking Time Series as Continuous-Time Trends and Events
L-SR1: Learned Symmetric-Rank-One Preconditioning
Information Flow Reveals When to Trust Language Models
AutoQRA: Joint Optimization of Mixed-Precision Quantization and Low-rank Adapters for Efficient LLM Fine-Tuning
Degradation-Aware Metric Prompting for Hyperspectral Image Restoration
DroneDINO: Towards Heterogeneous Routed Mixture of Experts for Drone-based Unified Object Detection
SoftMoE: Soft Differentiable Routing for Mixture-of-Experts in LLMs
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
LDARNet: DNA Adaptive Representation Network with Learnable Tokenization for Genomic Modeling
Trajectory-Level Speculative Decoding for Diffusion Language Models
Unlearning Isn’t Forgetting: Revealing Hidden Leakage in Class Unlearning Evaluations
SORA: Free Second Order Attacks in Fast Adversarial Training
The Truth Stays in the Family: Enhancing Contextual Truthfulness via Inherited Heads in Model Lineages
Provable Accuracy Collapse of Embedding-Based Representations under Dimensionality Mismatch
OmniShow: Orchestrating Multimodal Conditions for Human-Object Interaction Video Generation
HugRAG: Hierarchical Causal Knowledge Graph Design for RAG
Moving Out: Physically-grounded Human-AI Collaboration
Distinguishable Deletion: Unifying Knowledge Erasure and Refusal for Large Language Model Unlearning
Pseudo-Mallows for Efficient Probabilistic Preference Learning
Why DDIM Hallucinates More than DDPM: A Theoretical Analysis of Reverse Dynamics
Adaptive Volumetric Mechanical Property Fields Invariant to Resolution
Adaptive Utilization of Low-Rank Adaptation via Conditioned Gating
Stability-Aware Feature Design for Robust Watermark Detection in Machine-Generated Text
DecodeShare: Tracing the Shared Pathways of LLM Decode-Time Decisions
Beyond Temperature: Hyperfitting as a Late-Stage Geometric Expansion
Continual Segmentation under Joint Nonstationarity
Adaptively Grouped Contextual Bandits for Heterogeneous Human-AI Decision Making with Conformal Prediction Sets
Error Analysis of Discrete Flow with Generator Matching
Mitigating Perceptual Judgment Bias in Multimodal LLM-as-a-Judge via Perceptual Perturbation and Reward Modeling
Concept Concentration for Faithful Representation Intervention
Mining Tensor/Neuron-Level Sparsity to Maximize Mixture-of-Experts Potential in Post-Training and Inference
SciVideoBench: Benchmarking Scientific Video Reasoning in Large Multimodal Models
Perceptual Flow Network for Visually Grounded Reasoning
Stability Analysis of Sharpness-Aware Minimization
Sample from What You See: Visuomotor Policy Learning via Diffusion Bridge with Observation-Embedded Stochastic Differential Equation
LAPRAS : Learning-Augmented PRivate Answering for linear query Streams.
MLLM-4D: Towards Visual-based Spatial-Temporal Intelligence
QTALE: Quantization-Robust Token-Adaptive Layer Execution for LLMs
Helpful to a Fault: Measuring Illicit Assistance in Multi-Turn, Multilingual LLM Agents
Training-Trajectory-Aware Token Selection
Latent Laplace Diffusion for Irregular Multivariate Time Series
Self-Refining Video Sampling
How Do Language Models Speak Languages? A Case Study on Unintended Code-Switching
Causal-Adapter: Taming Text-to-Image Diffusion for Faithful Counterfactual Generation
Causally Evaluating the Learnability of Formal Language Tasks
SLIM: Secure and Efficient Inference for Large Language Models on Untrusted Devices via TEEs
Didactic to Constructive: Turning Expert Solutions into Learnable Reasoning
ClinTutor-R1: Advancing Scalable and Robust One-to-Many Alignment in Clinical Socratic Education
Modeling Hierarchical Thinking in Large Reasoning Models
TRACE: Toulmin-based Reasoning Assessment through Constructive Elements for LLM CoT Evaluation
Topology-Preserving Neural Operator Learning via Hodge Decomposition
Towards the Explainability of Temporal Graph Networks via Memory Backtracking and Topological Attribution
Training Data Efficiency in Multimodal Process Reward Models
On Stable Long-Form Generation: Benchmarking and Mitigating Length Volatility
$f$-Trajectory Balance: A Loss Family for Tuning GFlowNets, Generative Models, and LLMs with Off- and On-Policy Data
Saving Foundation Flow-Matching Priors for Inverse Problems
Credit Assignment via Neural Manifold Noise Correlation
UltraHorizon: Benchmarking LLM-Agent Capabilities in Ultra Long-Horizon Scenarios
Scaling Prompt Synthesis for Large Language Model Reasoning
Concept Removal for Frontier Image Generative Models
SparseInfer: Accelerating Large Language Model Inference with Semantics-Inspired Adaptive Sparse Activation
Towards Feedback-to-Plan Decisions for Self-Evolving LLM Agents in CUDA Kernel Generation
Optimal Top-$k$ Identification from Pairwise Comparisons
The Optimal Sample Complexity of Linear Contracts
Krause Synchronization Transformers
Conformal Policy Control
One LR Doesn’t Fit All: Heavy-Tail Guided Layerwise Learning Rates for LLMs
Identifying and Correcting Label Noise for Robust GNNs via Influence Contradiction
ZipMoE: Efficient On-Device MoE Serving via Lossless Compression and Cache-Affinity Scheduling
Eyes-on-Me: Scalable RAG Poisoning through Transferable Attention-Steering Attractors
RouterInterp: Understanding Superposed Specialisation in Mixture of Experts Routing
Search or Accelerate: Confidence-Switched Position Beam Search for Diffusion Language Models
New Algorithms for Fully-Dynamic k-center with Outliers
Enhancing Numerical Prediction in LLMs via Smooth MMD Alignment
Steering at the Source: Style Modulation Heads for Robust Persona Control
Approximating Drift-Diffusion Models for User Decisions under Nudging and External Information
Parametric Prior Mapping Framework for Non-stationary Probabilistic Time Series Forecasting
On the Convergence of Decentralized Stochastic Minimax Optimization Algorithm with Compressed Communication
Energy-based Compositional Diffusion Planning
MMBench-Live: A Continuously Evolving Benchmark for Multimodal Models
Measuring Intent Comprehension in LLMs
MedMamba: Multi-View State Space Models with Adaptive Graph Learning for Medical Time Series Classification
An Interactive Paradigm for Deep Research
Alignment Tampering: How Reinforcement Learning from Human Feedback Is Exploited to Optimize Misaligned Biases
HypoSpace: A Diagnostic Benchmark for Set-Valued Hypothesis Generation under Underdetermination and Sublinear Coverage Bounds
Reasoning Compartmentalization: Bridging the Concretization Gap via Abstraction-based Routing
Is Vibe Coding Safe? Benchmarking Vulnerability of Agent-Generated Code in Real-World Tasks
Beyond Static Allocation: Dynamic Sensitivity-Aware Fine-Tuning for Vision Transformers
Practical Mechanism for Fault-Tolerant Spiking Neural Networks via Simple Input Control Based on Learnable Fragmentation
MiniAppBench: Evaluating the Shift from Text to Interactive HTML Responses in LLM-Powered Assistants
VisionPulse: Dynamic Visual Sparsity for Efficient Multimodal Reasoning
PGC: Peak-Guided Calibration for Generalizable AI-Generated Image Detection
DataGuard: A Non-intrusive Dataset Auditing Framework via Differential Information Forensics
Stochastic Sparse Attention for Memory-Bound Inference
No More K-means: Single-Stage Sparse Coding for Efficient Multi-Vector Retrieval
The Expert Strikes Back: Interpreting Mixture-of-Experts Language Models at Expert Level
Mitigating Error Propagation in Low-Rank Approximation of Large Models via Distribution-Aware Whitening
LARFT: Closing the Cognition-Action Gap for Length Instruction Following in Large Language Models
Mind the Gap: Mixtures of Gaussians in Approximate Differential Privacy
Cross-Subject Modeling for Widefield Calcium Imaging via Atlas-Aligned Spatiotemporal Tokenization
Reasoning Structure of Large Language Models
On the Entropy Dynamics in Reinforcement Fine-Tuning of Large Language Models
Spatio-Temporal LLM: Reasoning about Environments and Actions
Circle-RoPE: Cone-like Decoupled Rotary Positional Embedding for Vision-Language Models
Pianist Transformer: Towards Expressive Piano Performance Rendering via Scalable Self-Supervised Pre-Training
Anchor-Final Self-Supervision Drives Hallucination-Aware Optimization in Large Vision-Language Models
Neural-HSS: Hierarchical Semi-Separable Neural PDE Solver
Attribution-Guided and Coverage-Maximized Pruning for Structural MoE Compression
The Sign Estimator: Preference Modeling for LLM Alignment under Heterogeneity
SafeLab: An Interactive High-Fidelity Benchmark for Embodied Safety in Scientific Robotics
One Bug, Hundreds Behind: LLMs for Large-Scale Bug Discovery
Latent Representation Alignment for Offline Goal-Conditioned Reinforcement Learning
Statistical Early Stopping for Reasoning Models
Mixture Prototype Flow Matching for Open-Set Supervised Anomaly Detection
SpatialReward: Bridging the Perception Gap in Online RL for Image Editing via Explicit Spatial Reasoning
FLAG: Foundation model representation with Latent diffusion Alignment via Graph for spatial gene expression prediction
A Linearly Convergent Proximal Subgradient Algorithm for Sparse Portfolio Optimization with Transaction Cost
Is Your Diffusion Sampler Actually Correct? A Sampler-Centric Evaluation of Discrete Diffusion Language Models
Probing the Geometry of Diffusion Models with the String Method
TRACER: Trajectory Risk Aggregation for Critical Episodes in Agentic Reasoning
Dynamic Programming for Epistemic Uncertainty in Markov Decision Processes
On Information Self-Locking in Reinforcement Learning for Active Reasoning
PCGS: Deblurring 3D Gaussian Splatting with Patch Comparison
Semantic Impact–Driven Visual Scheduling in Vision-Language Models
CLASP: Online learning algorithms for Convex Losses And Squared Penalties
SuCo: Sufficiency-guided Continuous Adaptive Reasoning
VLM-RobustBench: A Comprehensive Benchmark for Robustness of Vision-Language Models
Beyond Extrapolation: Knowledge Utilization Paradigm with Bidirectional Inspiration for Time Series Forecasting
Propose, Solve, Verify: Self-Play Through Formal Verification
UB-SMoE: Universally Balanced Sparse Mixture-of-Experts for Resource-adaptive Federated Fine-tuning of Foundation Models
TRACE: Trajectory Recovery for Continuous Mechanism Evolution in Causal Representation Learning
Sample Complexity Bounds for Robust Mean Estimation with Mean-Shift Contamination
Entropy-aware Span-Constrained Optimal Transport for Robust Cross-Tokenizer Knowledge Distillation
A Positive Case for Faithfulness: Explanations Help Predict Model Behavior
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
Asymmetric Prompt Weighting for Reinforcement Learning with Verifiable Rewards
Large-scale Uncertainty Quantification for Latent Variable Models Using Subsampling Markov Chain Monte Carlo
Curriculum-Guided Layer Scaling for Language Model Pretraining
Telescope: Improving Zero Shot Detection of LLM Generated Content By Measuring Token Repetition Probability
PolarDepth: Monocular Transparent Object Depth from Polar-Physics Priors
DocVAL: Validated Chain-of-Thought Distillation for Grounded Document VQA
Looking Locally: Object-Centric Vision Transformers as Foundation Models for Efficient Segmentation
ParEVO: Synthesizing Code for Irregular Data: High-Performance Parallelism through Agentic Evolution
Post-Hoc Merging is Not Enough: Many-Shot Model Merging with Loss-Gap Balancing
The Quality-Utility Paradox: Why High-Reward Data Impairs Small Model Reasoning
Revisiting Padded Transformer Expressivity: Which Architectural Choices Matter and Which Don't
DecAEvolve: Decompose, Adapt, and Evolve, or, Three Pillars of Effective LLM-based Scientific Equation Discovery
G$^2$RPO: Geometric GRPO; Escaping LLM's Reasoning Rut to Break Accuracy--Entropy Trade-off
REViT: Roto-reflection Equivariant Convolutional Vision Transformer
LLM-based Embeddings: Attention Values Encode Sentence Semantics Better Than Hidden States
VocSim A Training-free Benchmark for Zero-shot Content Identity in Single-source Audio
Star Elastic: Many-in-One Reasoning LLMs with Efficient Budget Control
EvoMAS: Heuristics in the Loop—Evolving Smarter Agentic Workflows
Block Rotation is All You Need for MXFP4 Quantization
On the Generalization Gap in Self-Evolving Language Model Reasoning
Swift-SVD: Theoretical Optimality Meets Practical Efficiency in Low-Rank LLM Compression
When Labelers Stay Silent: The Power of Ties in Cost-Effective Preference Learning
Optimal Statistical Guarantees for Diffusion Models on Low-Dimensional, Multi-Modal Data
On Uniform Error Bounds for Kernel Regression under Non-Gaussian Noise
LiMuon: Light and Fast Muon Optimizer for Large Models
Robust Multi-View Fusion via Prototype-Anchored Unbalanced Optimal Transport
PSG-Nav: Probabilistic Scene Graph Navigation via Multiverse Decision Making
SWE-MiniSandbox: Container-Free Reinforcement Learning for Building Software Engineering Agents
CatFlow: Co-generation of Slab-Adsorbate Systems via Flow Matching
Textual Stochastic Gradient Descent: Discrete Optimization of External Memory for Reasoning Language Agents
Momentum Further Constrains Sharpness at the Edge of Stochastic Stability
Unbiased Alignment for Large Language Models with Noisy Preferences
Efficient Training-Free Multi-Token Prediction via Embedding-Space Probing
Machine Learning Hamiltonians are Accurate Energy-Force Predictors
Dataset Distillation Efficiently Encodes Low-Dimensional Representations from Gradient-Based Learning of Non-Linear Tasks
Hyperbolic Associative Memory Networks
Geometry-Aware Image Flow Matching
RePro: Training Language Models to Faithfully Recycle the Web for Pretraining
PRISM: Demystifying Retention and Interaction in Mid-Training
The Extra Tokens Matter: Disentangled Representation Learning with Vision Transformers
World-R1: Reinforcing 3D Constraints for Text-to-Video Generation
Fast k-means Seeding Under The Manifold Hypothesis
WildCat: Near-Linear Attention in Theory and Practice
From Outcomes to Actions: Leveraging Hindsight for Long-Horizon Language Agent Training
A Deep Learning Model of Mental Rotation Informed by Interactive VR Experiments
FairSSL: Fair Multimodal Self-Supervised Learning
Calibrating Decision Robustness via Inverse Conformal Risk Control
From Poisoned to Aware: Fostering Backdoor Self-Awareness in LLMs
Online Learning with Recency: Algorithms for Sliding-window Streaming Multi-armed Bandits
PLANTAIN: Plan-Answer Interleaved Reasoning
Learning Junta Distributions, Quantum Junta States, and QAC$^0$ Circuits
Bridging On-Device and Cloud LLMs for Collaborative Reasoning: A Unified Methodology for Local Routing and Post-Training
STAR-KV: Low-Rank KV Cache Compression via Soft Thresholding for Adaptive Rank Control
WinQ: Accelerating Quantization-Aware Training of Large Language Models around Saddle Points
VideoTemp-o3: Harmonizing Temporal Grounding and Video Understanding in Agentic Thinking-with-Videos
The Value Function Semi-Algebraic Set in Partially Observable Markov Decision Processes
TextMesh4D: Zero-shot Text-to-4D Mesh Generation
(Doubly) Exponential Lower Bounds for Follow the Regularized Leader in Potential Games
ConServe: Fine-Grained GPU Harvesting for LLM Online and Offline Co-Serving
Steer Where It Matters: Token-Level Visual-Sensitivity Steering for LVLMs Hallucination Mitigation
TaRO: Temporal-Aware Reasoning Optimization for Video Temporal Grounding
OTora: A Unified Red Teaming Framework for Reasoning-Level Denial-of-Service in LLM Agents
On the Theory of Continual Learning with Gradient Descent for Neural Networks
Sample Efficient Full-Finetuning of Generative Control Policies
Use What You Know: Causal Foundation Models with Partial Graphs
Long-Context Modeling with Dynamic Hierarchical Sparse Attention for Memory-Constrained LLM Inference
Learning syntax without semantics: Disentangled tiny language models
Quadratically Regularized Optimal Transport: Localization Bounds and Affine Case Analysis
Inference-time optimization for experiment-grounded protein ensemble generation
ConPress: Learning Efficient Reasoning from Multi-Question Contextual Pressure
Mitigating Error Accumulation in Continuous Navigation via Memory-Augmented Kalman Filtering
Skip a Layer or Loop It? Learning Program-of-Layers in LLMs
Compass-RoPE: Isotropic Rotary Position Embeddings for Vision Transformers
Stabilizing Native Low-Rank LLM Pretraining
LEGO: An LLM-Enabled Hierarchical Optimizer for Tensor Computation Graphs with Structure-Aware Search and Compositional Synthesis
L2G-NET: Local to Global Spectral Graph Neural Networks via Cauchy Factorizations
Learning Decentralized LLM Collaboration with Multi-Agent Actor Critic
Scaling-Aware Adapter for Structure-Grounded LLM Reasoning
CMI-RewardBench: Evaluating Music Reward Models with Compositional Multimodal Instruction
Meta-learning Structure-Preserving Dynamics
GEM: Geometric Entropy Mixing for Optimal LLM Data Curation
A Hitchhiker's Guide to Poisson Gradient Estimation
Memory Savings at What Cost? A Study of Alternatives to Backpropagation
KnapSpec: Self-Speculative Decoding via Adaptive Layer Selection as a Knapsack Problem
From Seeing to Thinking: Decoupling Perception and Reasoning Improves Post-Training of Vision-Language Models
Safeguarded Stochastic Polyak Step Sizes for Non-smooth Optimization: Robust Performance Without Small (Sub)Gradients
Credit-assigned Policy Gradient for Early Stage Retrieval in Two-stage Ranking
Revisiting Parameter-Based Knowledge Editing in Large Language Models: Theoretical Limits and Empirical Evidence
Embedding Hybrid Systems into Continuous Latent Vector Fields
Reinforcement Learning with Action-Triggered Observations
Flow Equivariant World Models: Structured Memory for Dynamic Environments
Divide and Conquer: Reliable Multi-View Evidential Learning for Deepfake Detection
Rethinking Calibration for Early-Exit Neural Networks
OmniSapiens: A Foundation Model for Social Behavior Processing via Heterogeneity-Aware Relative Policy Optimization
Generative Modeling with Probabilistic Constraints
Zero Sum SVD: Balancing Loss Sensitivity for Low Rank LLM Compression
How to Fine-Tune a Reasoning Model? A Teacher–Student Cooperation Framework to Synthesize Student-Consistent SFT Data
A Fully First-Order Layer for Differentiable Optimization
The Theory and Practice of MAP Inference over Non-Convex Constraints
HaloProbe: Bayesian Detection and Mitigation of Object Hallucinations in Vision-Language Models
Pushing the Boundaries of Natural Reasoning: Interleaved Bonus from Formal-Logic Verification
Demystifying Scientific Problem-Solving in LLMs by Probing Knowledge and Reasoning
Layer-wise Gradient Disentanglement: Decoupling Semantics and Preferences in Direct Preference Optimization
Evolving Quantitative Reasoning through Self-Play in Digital Twin Markets
Entropy-Aware Dynamic KV Cache Sparsification for Autoregressive Image Generation and Editing
Probabilistic Robustness Certificates against Adversarial Attacks
Bridging Functional Correctness and Runtime Efficiency Gaps in LLM-Based Code Translation
Small Generalizable Prompt Predictive Models Can Steer Efficient RL Post-Training of Large Reasoning Models
BRIDGE: Triangular Fixed-Point Refinement for Long-Horizon Persona Consistency
Normality Calibration in Semi-supervised Graph Anomaly Detection
Inconsistency-Aware Minimization: Improving Generalization with Unlabeled Data
Diffusion Language Model Parallel Decoding via Product-of-Experts Bridge
Spatial Memory for Out-of-Vision Manipulation in Vision-Language-Action
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
Evolution Strategies at Scale: LLM Fine-Tuning Beyond Reinforcement Learning
Real-Time Aligned Reward Model beyond Semantics
DRL-STAF: A DRL Framework for State-aware Forecasting of Complex Multivariate Hidden Markov Process
Wasserstein Geometry-Aware Adaptive Control via Meta-Learning
Budget-Feasible Mechanisms for Submodular Welfare Maximization in Procurement Auctions
Locally Coherent Parallel Decoding in Diffusion Language Models
ReMoE: Boosting Expert Reuse through Router Fine-Tuning in Memory-Constrained MoE LLM Inference
UniScale: Adaptive Unified Inference Scaling via Online Joint Optimization of Model Routing and Test-Time Scaling
Capacity-Agnostic Parameter Isolation for Continual Graph Learning
On Path to Multimodal Historical Reasoning: HistBench and HistAgent
LLM-MatLogic: Executable Exchange Contracts for Knowledge-Graph Query Answering with Scoped Negation
SorryDB: Can AI Provers Complete Real-World Lean Theorems?
Position: Federated Learning is a Lens towards a Democratized Future for the Scaling Law Era
Best of Both Worlds: Multimodal Reasoning and Generation via Unified Discrete Flow Matching
Geometrically Constrained Stenosis Editing in Coronary Angiography via Entropic Optimal Transport
SPHERE: Mitigating the Loss of Spectral Plasticity in Mixture-of-Experts for Deep Reinforcement Learning
CAOS: Conformal Aggregation of One-Shot Predictors
CoEvol-NO: State and Coordinate Co-Evolution with an Error-Driven Predictor-Corrector Paradigm for Neural Operator Transformer
BPDQ: Bit-Plane Decomposition Quantization on a Variable Grid for Large Language Models
CoIRL-AD: Collaborative-Competitive Imitation-Reinforcement Learning in Latent World Models for Autonomous Driving
Gauge-Equivariant Graph Networks via Self-Interference Cancellation
An Approximation Algorithm for Graph Label Selection
Evaluating and Rewarding LALMs for Expressive Role-Play TTS via Mean Continuation Log-Probability
Why Agentic Theorem Prover Works: A Statistical Provability Theory of Mathematical Reasoning Models
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
Inference of Online Newton Methods with Nesterov's Accelerated Sketching
Dimension-Independent Convergence of Underdamped Langevin Monte Carlo in KL Divergence
Decomposition-Based Modular Conformal Prediction for Two-Stage Modeling
Evaluating Robustness of Reasoning Models on Parameterized Logical Problems
Through the Stealth Lens: Attention-Aware Defenses Against Poisoning in RAG
Sharper Generalization Guarantees for Asynchronous SGD: Beyond Lipschitzness, Smoothness and Data Homogeneity
Position: Epistemic uncertainty estimation methods are fundamentally incomplete
Mantis: Lightweight Foundation Model for Time Series Classification
Provable Sample Efficiency of Curriculum Post-Training for Transformer Reasoning
A Task-centric Theory for Iterative Self-Improvement with Easy-to-Hard Curricula
Protein Language Model Embeddings Improve Generalization of Implicit Transfer Operators
Constrained Adaptive Rejection Sampling
Float8@2bits: Entropy Coding Enables Data-Free Model Compression
Test-time Generalization for Physics through Neural Operator Splitting
Iterated Population Based Training with Task-Agnostic Restarts
Knothe-Rosenblatt Quantile Regression for Risk-sensitive Multi-objective Reinforcement Learning
NeurOCNN: A Neural-Operator-Based Model for Physiological Time Series
Finite and Corruption-Robust Regret Bounds in Online Inverse Linear Optimization under M-Convex Action Sets
Seeing to Generalize: How Visual Data Corrects Binding Shortcuts
MaMi-HOI: Harmonizing Global Kinematics and Local Geometry for Human-Object Interaction Generation
GOTabPFN: From Feature Ordering to Compact Tokenization for Tabular Foundation Models on High-Dimensional Data
Transformers learn factored representations
Efficient and Unbiased Sampling from Boltzmann Distributions via Variance-Tuned Diffusion Models
Factor-Wise Homogeneity of Slot-Attention for Continual Object-Centric Learning
cuRegOT: A GPU-Accelerated Solver for Entropic-Regularized Optimal Transport
Hista and Numca: Estimate State Value Effectively for Large Language Model Reinforcement Learning
Weak Diffusion Priors Can Still Achieve Strong Inverse-Problem Performance
A Call to Lagrangian Action: Learning Population Mechanics from Temporal Snapshots
GraphFLEx: Unsupervised Structure Learning $\underline{\text{F}}$ramework for $\underline{\text{L}}$arge $\underline{\text{Ex}}$panding $\underline{\text{Graph}}$s
Endogenous Resistance to Activation Steering in Language Models: Evidence for Internal Consistency Monitoring in Llama-3.3-70B
KAGE-Bench: Fast Known-Axis Visual Generalization Evaluation for Reinforcement Learning
Nonparametric Distribution Regression Re-calibration
Performative Policy Gradient: Optimality in Performative Reinforcement Learning
BLIPs: Bayesian Learned Interatomic Potentials
Transformers Efficiently Perform In-Context Logistic Regression via Normalized Gradient Descent
Minimax Optimal Strategy for Delayed Observations in Online Reinforcement Learning
Collaborative Disagreement Resolution for Scalable Oversight
REAL: Resolving Knowledge Conflicts in Knowledge-Intensive Visual Question Answering via Reasoning-Pivot Alignment
Imposing Boundary Conditions on Neural Operators via Learned Function Extensions
Training-Free Bayesian Filtering with Generative Emulators
Symmetry Reveals the In-Context Classifier: Transformers Implement Mean-Shift Dynamics
Position: Invisible Tokens, Visible Bills: The Urgent Need to Audit Hidden Operations in Opaque LLM Services
OBCache: Optimal Brain KV Cache Pruning for Efficient Long-Context LLM Inference
Position: The Inevitable Transition to Machine Learning in Quantum Chemistry
Breaking the Factorization Barrier in Diffusion Language Models
When does predictive inverse dynamics outperform behavior cloning?
Position: Reasoning After Perception Means Reasoning Without Vision
Accordion-Thinking: Self-Regulated Step Summaries for Efficient and Readable LLM Reasoning
Prediction-Powered Adaptive Inference with Pretrained AI Models for Contextual Bandits
RealisMotion: Decomposed Human Motion Control and Video Generation in the World Space
RSTR: Reducing SpatioTemporal Redundancy in Diffusion Transformers
On the Collapse of Generative Paths: A Criterion and Correction for Diffusion Steering
XYZFlow: Scaling Multidimensional Shortcut Flows for Efficient Generative Modeling
Direct 3D-Aware Object Insertion via Decomposed Visual Proxies
MindZero: Learning Online Mental Reasoning With Zero Annotations
Position: Collaborative Agentic AI Needs Interoperability Across Ecosystems
LieStoNet: Learning Lie Symmetries from Spatiotemporal Data for Stochastic Dynamical Systems
Doubly Outlier-Robust Online Infinite Hidden Markov Model
GFedCL: Graph-Based Federated Continual Learning with Spatial and Temporal Awareness
Weight Updates as Activation Shifts: A Principled Framework for Steering
Position: Explanation Stability Is a Property of the Model–Method Pair, Not the Model
Is Training Necessary for Anomaly Detection?
What Does Flow-Matching Bring to TD-Learning?
HoloFair: Unified T2I Fairness Evaluation and Fair-GRPO Debiasing
Refining Context-Entangled Content Segmentation via Curriculum Selection and Anti-Curriculum Promotion
Strategic Navigation or Stochastic Search? How Agents and Humans Reason Over Document Collections
How Hard Can It Be? Hardness-Aware Multi-Objective Unlearning
Learning Hamiltonian Dynamics at Scale: A Differential-Geometric Approach
Semantic-Enriched Latent Visual Reasoning
Well-Posed KL-Regularized Control via Wasserstein and Kalman–Wasserstein KL Divergences
Statistical Learning Theory in Lean 4: Empirical Processes from Scratch
On the Power of Source Screening for Learning Shared Feature Extractors
CoverPruneGS: Coverage-Preserving Structured Pruning for Hierarchical 3D Gaussian Splatting from Sparse-View Monocular Videos
MixFP4: Extending NVFP4 to Mixed Micro-Format via Scale-Bit Reuse and Tensor Core Co-design
PEARL: Differentially Private and Entropy-Aware Regulated Language Generation
Unleashing the Representational Power of Fourier Shapes for Attacking Infrared Object Detection
Towards Understanding the Dynamics of Low-Rank Adaptation
Hyperspectral Image Fusion with Spectral-Band and Fusion-Scale Agnosticism
A Spiking Heterogeneous Harmonic Resonate-and-Fire State Space Model for Time Series
CountsDiff: A diffusion model on the natural numbers for generation and imputation of count-based data
Butterworth as Attention: Anisotropic Spectral Gating for Pansharpening
Semantic-Aware Motion Encoding for Topology-Agnostic Character Animation
FairJudge : An Adaptive, Debiased, and Consistent LLM-as-a-Judge
Spatially-Regularized Entropy for Discriminative Token Merging in Fine-Grained Re-Identification
Beyond Heuristics: Learnable Density Control for 3D Gaussian Splatting
UnHype: CLIP-Guided Hypernetworks for Dynamic LoRA Unlearning
Large-capacity and Receiver Authenticable Generative Image Steganography
Learning Credal Ensembles via Distributionally Robust Optimization
Representation Drift Compensation: A Zero-Cost Enhancement for LLM Decomposition
Fully Zero-Shot Image Dehazing
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
Fix Before Search: Benchmarking Agentic Visual Query Pre-processing in Multimodal Retrieval-augmented Generation
Counterfactual Bootstrap for Robust Meta-Reinforcement Learning
PADS-TAL: Padding-Annealed Diffusion Sampling in Text-Aware Latent Space for Robust and Diverse Text-to-Music Generation
Light Up Your Face: A Physically Consistent Dataset and Diffusion Model for Face Fill-Light Enhancement
Should I Have Expressed a Different Intent? Counterfactual Generation for LLM-Based Autonomous Control
Towards Realistic Lifelong Re-identification: Identity Recurrence with Changing Clothes
MonoScale: Scaling Multi-Agent System with Monotonic Improvement
Think in Latent, Explain in Language: Self-Explainable Latent Reasoning
Log-Normal Multiplicative Dynamics for Stable Low-Precision Deep Learning
CLINIC : Evaluating Multilingual Trustworthiness in Language Models for Healthcare
Two-Layer Linear Auto-Regressive Models Estimate Latent States
Faults in Our Formal Benchmarking: Dataset Defects and Evaluation Failures in Lean Theorem Proving
TRIP-Bench: A Benchmark for Long-Horizon Interactive Agents in Real-World Scenarios
Diffuse to Detect: Bi-Level Sample Rebalancing with Pseudo-Label Diffusion for Point-Supervised Infrared Small-Target Detection
$\mu$pscaling small models: Principled warm starts and hyperparameter transfer
Evaluating bivariate causal statements based on mutual compatibility
Structure-Aware Consistency Priors for Shape from Polarization in Complex Media
Beyond Pixels: Mining Compressed Domain Artifacts for Efficient AI-Generated Video Detection
SHERPA: Fine-tuning Segment Anything Models with Task-relevant Guidance
Diversity-Driven Offline Multi-Objective Optimization via Bi-Level Pareto Set Learning
Improving Adversarial Robustness of Attribution via Implicit Regularization
Rule2DRC: Benchmarking LLM Agents for DRC Script Synthesis with Execution-Guided Test Generation
Towards Cold-Start Drafting and Continual Refining: A Value-Driven Memory Approach with Application to NPU Kernel Synthesis
Equivalence of Context and Parameter Updates in Modern Transformer Blocks
Reusing Trajectories in Policy Gradients Enables Fast Convergence
Deep Residual Injection for Full-Spectrum Forensic Signal Perception in Multimodal Large Language Models
Instance-Dependent Continuous-Time Reinforcement Learning via Maximum Likelihood Estimation
Cheap2Rich: A Multi-Fidelity Framework for Data Assimilation and System Identification of Multiscale Physics - Rotating Detonation Engines
AgentWebBench: Benchmarking Multi-Agent Coordination in Agentic Web
AVGen-Bench: A Task-Driven Benchmark for Multi-Granular Evaluation of Text-to-Audio-Video Generation
Alleviating Sparse Rewards by Modeling Step-Wise and Long-Term Sampling Effects in Flow-Based GRPO
Affine-Scaled Attention: Towards Flexible and Stable Transformer Attention
Learn-to-learn on Arbitrary Textual Conditioning: A Hypernetwork-Driven Meta-gated LLM
Why Do We Need Warm-up? A Theoretical Perspective
Sentinel-VLA: A Metacognitive VLA Model with Active Status Monitoring for Dynamic Reasoning and Error Recovery
A Very Big Video Reasoning Suite
IQA-Spider: Unifying Reasoning, Grounding, and Referring for Multi-Granularity Image Quality Assessment
Bridging the Stability-Expressivity Gap: Synthetic Data Scaling and Preference Alignment for Low-Resource Spoken Language Models
Bridging the Grounding Gap in VideoQA via Typed Memory for Language-based Belief-State Reasoning
Online Linear Programming for Multi-Objective Routing in LLM Serving
RAST-MoE-RL: A Regime-Aware Spatio-Temporal MoE Framework for Deep Reinforcement Learning in Ride-Hailing
SpaCeFormer: Space-Curve Transformer for Open-Vocabulary 3D Instance Segmentation without Proposals
Learning Generalized Trackers with Elastic Token Budgets
QuantWear: Quantum-scale Wear Particle Detection for Jet Engine Diagnosis
Learning the Minimum Action Distance
Transitive Representation Learning Enhances Histopathology Annotation
Navigating the Flatlands: Dual Adaptive Sharpness-Aware Minimization for Domain Generalization
Open-Text Aerial Detection: A Unified Framework For Aerial Visual Grounding And Detection
MutAtlas: A PDB-Wide Energy-Guided Atlas of Protein Mutation Effects
Incremental BPE Tokenization
Density-Aware Translation of Spurious Correlations in Zero-Shot VLMs
Learning Graph Foundation Models on Riemannian Graph-of-Graphs
Debiased Model-based Representations for Sample-efficient Continuous Control
Foundation Inference Models for Ordinary Differential Equations
Learning to Perceive the World Through Control: Empowerment-Based Representation Learning
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
PersistBench: When Should Long-Term Memories Be Forgotten by LLMs?
Supervise Less, See More: Training-free Nuclear Instance Segmentation with Prototype-Guided Prompting
Trainable Nonexpansive Denoisers for Contractive Image Reconstruction
Towards Trustworthy and Identifiable Virtual Face Generation
Rethinking Low-Confidence Pseudo Labels: Influence-Aware Semi-Supervised Fine-Tuning for Hyperspectral Change Detection
CGSVD: Cascaded Granular Singular Value Decomposition for Large Language Model Compression
SimGFM: Simplifying Discrete Flow Matching for Graph Generation
Learning Rewrite-Invariant Reasoning with Targeted Alternation Training
Universal Reasoner: A Single, Composable Plug-and-Play Reasoner for Frozen LLMs
Pix2Key: Controllable Open-Vocabulary Retrieval with Semantic Decomposition and Self-Supervised Visual Dictionary Learning
Optimizing Diversity and Quality through Base-Aligned Model Collaboration
Stabilizing Reinforcement Learning for Diffusion Language Models
ANCHOR: Automated Alignment Auditing for CLI Agents on Real-World Harm
OSCS: Online Selection with Provable FAR Control for LLM Safety
Causal Preference Elicitation
Lottery Prior: Randomized Neural Compression for Zero-Shot Inverse Problems
Adaptive Querying with AI Persona Priors
Peer-Preservation in Frontier Models
PCRNet: Phase-aware Complex Refinement Network for EEG-based Auditory Attention Decoding
Expandable, Compressible, Mineable: Open-World Thermal Infrared Image Restoration
MM-Spectrum: Multimodal Multi-spectral Molecular Structural Elucidation with a Stable MoE Framework
Towards Resource-Efficient LLMs: End-to-End Energy Accounting of Distillation Pipelines
Genome-Factory: A Library for Tuning, Deploying, and Interpreting Genomic Foundation Models
PyHealth 2.0: A Comprehensive Open-Source Toolkit for Accessible and Reproducible Clinical Deep Learning
Stable Localized Conformal Prediction via Transduction
High-accuracy and dimension-free sampling with diffusions
A Short and Unified Convergence Analysis of the SAG, SAGA, and IAG Algorithms
Box Thirding: Anytime Best Arm Identification under Insufficient Sampling
WBMM: Windowed Batch Matrix Multiplication for Efficient Large Receptive Field Convolution
Learning Cardiac Latent Representations in Vectorcardiogram Space
Beyond Static Endpoints: Tool Programs as an Interface for Flexible Agentic Web Services
DNA: Uncovering Universal Latent Forgery Knowledge
GSFixer: Improving 3D Gaussian Splatting with Reference-Guided Video Diffusion Priors
M+Adam: Low-Precision Training via Mantissa–Exponent Optimization
Differentiable Conformal Training for LLM Reasoning Factuality
HelioX: A GPU-Native Framework for Simulation and Training of Biophysically Detailed Networks
FlatLab: A Unified Methodology Framework and Simulation-Based Benchmark for Robotic Manipulation of Flat Objects
Exact Unlearning in Reinforcement Learning
Debate2Create: Robot Co-design via Multi-Agent LLM Debate
From Abstraction to Instantiation: Learning Behavioral Representation for Vision-Language-Action Model
PlugGuard: A Streaming Safeguard for Large Models via Latent Dynamics-Guided Risk Detection
HDFlow: Hierarchical Diffusion-Flow Planning for Long-horizon Tasks
Focus-Then-Contact: Speeding Up Robotic Contact-Rich Task Learning with Affordance-Guided Real-World Residual Reinforcement Learning
GAE: Unleashing Physical Potential of VLM with Generalizable Action Expert
SCALE: Self-uncertainty Conditioned Adaptive Looking and Execution for Vision-Language-Action Models
Scalable and Differentiable Point-Cloud Registration Using Maximum Mean Discrepancy
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
LiftQuant: Continuous Bit-Width Control for Pareto-Optimal LLM Deployment
Learning Protein Structure-Function Relationships through Knowledge-guided Representation Decomposition
Robust Stochastic Gradient Posterior Sampling with Lattice Based Discretisation
XR-1: Towards Versatile Vision-Language-Action Models via Learning Unified Vision-Motion Representations
Neural Implicit Action Fields: From Discrete Waypoints to Continuous Functions for Vision-Language-Action Models
VLANeXt: Recipes for Building Strong VLA Models
Dual-Stream Diffusion for World-Model Augmented Vision-Language-Action Model
DynVLA: Learning World Dynamics for Action Reasoning in Autonomous Driving
Steady-State Behavior of Constant-Stepsize Stochastic Approximation: Gaussian Approximation and Tail Bounds
Learning Permutation Distributions via Reflected Diffusion on Ranks
Distinguishing Imitation Error from Intrinsic Motion Learning Difficulty
Breaking the Reversal Curse in Autoregressive Language Models via Identity Bridge
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 Face Recognition
When Replanning Becomes the Bottleneck: Budgeted Replanning for Embodied Agents
Plan in Sandbox, Navigate in Open Worlds: Learning Physics-Grounded Abstracted Experience for Embodied Navigation
Embodied-DETR: End-to-End Temporal 3D Object Detection in Egocentric Views
Multi-Objective Learning for Diffusion Models: A Statistical Theory under Semi-Supervised Learning
Vision-Language-Action Pretraining from Large-Scale Human Videos
Embodiment-Conditioned Mixture of Experts Increases the Evolvability of Robots
RoboFlow4D: A Lightweight Flow World Model Toward Real-Time Flow-Guided Robotic Manipulation
DeepSight: Long-Horizon World Modeling via Latent States Prediction for End-to-End Autonomous Driving
VEQ: Modality-Adaptive Quantization for MoE Vision-Language Models
A Generalist Pair-wise Progress Critic Model for Vision-Language-Action Robots
Joint Navigation and Manipulation Planning with 3D Interaction Chains
Incorporating Importance Weighting in Optimal Transport Based Domain Alignment
RoboOmni: Actions Are Just Another Modality for Your Vision-Language Models
EMFormer: Efficient Multi-Scale Transformer for Accumulative Context Weather Forecasting
Hydra-Nav: Object Navigation via Adaptive Dual-Process Reasoning
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
DyGRO-VLA: Cross-Task Scaling of Vision–Language–Action Models via Dynamic Grouped Residual Optimization
Reading Between the Tokens: Improving Preference Predictions through Mechanistic Forecasting
Ranking Time Series using a Time Warping Ideal Point Model
BioFormer: Rethinking Cross-Subject Generalization via Spectral Structural Alignment in Biomedical Time-Series
A Unified Sparse Attention via Multi-Granularity Compression
Bootstrapped Exploration with Causal Reasoning: A Training Paradigm for Adaptive Forecasting Agent
What if Tomorrow is the World Cup Final? Counterfactual Time Series Forecasting with Textual Conditions
CombinationTS: A Modular Framework for Understanding Time-Series Forecasting Models
Lower Complexity Bounds for Nonconvex-Strongly-Convex Bilevel Optimization with First-Order Oracles
KUMA: A Novel Framework with Koopman Separation and Efficient Multilevel Extraction in Time Series Forecasting
Words Towards Explainability: Caption Label-Free Learning via Dual Loop Agentic Time Series Captioning
Time Series Reasoning via Process-Verifiable Thinking Data Synthesis and Scheduling for Tailored LLM Reasoning
Channel Adapter for Time Series Foundation Models in Zero-Shot Multivariate Forecasting
TF-FACE: Time-Frequency Fusion Learning via Frequency-Domain Adaptive and Controllable Enhancement for Trajectory Prediction
Gradient Regularization Prevents Reward Hacking in Reinforcement Learning from Human Feedback and Verifiable Rewards
“Do Diffusion Models Dream of Electric Planes?” Discrete and Continuous Simulation-Based Inference for Aircraft Design
3D-DLP: Self-supervised 3D Object-centric Scene Representation Learning
Geometric Flow Grounding: A Unified Manifold Decoupling Framework for Dynamics Discovery and Verification
EnsembleVLA: Ensemble Learning for Vision-Language Action Models
SKETCH: Semantic Key-Point Conditioning for Long-Horizon Vessel Trajectory Prediction
Distributionally Robust Reinforcement Learning with Human Feedback
Deep Trajectory Supervision: Deep Supervision Strikes Back
Holonomy Grid Codes for Generalisation Under Directed Actions
Off-Policy Evaluation for Missingness-Aware Policies in MDPs with Rewards Missing Not at Random
AOrchestra: Automating Sub-Agent Creation for Agentic Orchestration
R1-SyntheticVL: Is Synthetic Data from Generative Models Ready for Multimodal Large Language Model?
The Two-Hump Problem: Bridging the Difficulty Gap in Mathematical Reinforcement Learning
Dreaming in Code for Curriculum Learning in Open-Ended Worlds
Trust-Region Diffusion Policies for Massively Parallel On-Policy RL
Milestone-Guided Policy Learning for Long-Horizon Language Agents
Scalable Traffic Signal Control with Shared Policy Framework
Transferable Reinforcement Learning via Probabilistic Latent Embeddings and Dynamic Policy Adaptation for Sim-to-Real Deployment
Active Curriculum Refinement for Reinforcement Learning
Multi-view Consistent Latent Action Learning for World Modeling and Control
CFPO : Counterfactual Policy Optimization For Multimodal Reasoning
Learning Transferable Interaction Primitives from Game Videos for Humanoids
Beyond the Proxy: Trajectory-Distilled Guidance for Offline GFlowNet Training
Conformal Prediction for Early Stopping in Mixed Integer Optimization
Threat2Traffic: Multi-Agent Environment Synthesis for Malware Traffic Generation from Threat Intelligence
Geometry-Misalignment in Distributional Learning
BM^2: Coupled Schrödinger Bridge Matching
PipeSD: An Efficient Cloud-Edge Collaborative Pipeline Inference Framework with Speculative Decoding
Multi-Accurate CATE is Robust to Unknown Covariate Shifts
CANDI: Hybrid Discrete-Continuous Diffusion Models
Solving Time-Dependent Differential Equations with Physical Dynamical Systems
Markovian Projection of Star-Shaped Diffusion for Exponential Family Distributions
Bio-Vision-Inspired Spiking Neural Networks for Object Detection with Event Cameras
FedRGL: Robust Federated Graph Learning under Label Noise
Don't Ignore the Tail: Decoupling top-K Probabilities for Efficient Language Model Distillation
Confidence is Not Universal: Task-Dependent Calibration and Emergent Behavior in LLMs
Removing Noise, not Finding Gold: Quality Filtering for Large-Scale Pretraining
AgentLAB: Benchmarking LLM Agents against Long-Horizon Attacks
Can vision language models learn intuitive physics from interaction?
VFMF: Dense Forecasting by Generating Foundation Model Features
Positive-Unlabeled Learning with Extreme Scarcity of Labeled Positives
From Prior to Pro: Efficient Skill Mastering via Distribution Contractive RL Finetuning
From Coarse to Fine: Deep Prototype Refinement Network for Few-Shot Point Cloud Semantic Segmentation
FedARC: Anchor-Guided Residual Compensation for Data and Model Heterogeneous Federated Learning
DreamDojo: A Real-Time Robot World Model from Large-Scale Human Videos
Understanding Private Learning From Feature Perspective
Optimal Transport for Reward Modeling from Noisy Feedback
Decomposing the Basic Abilities of Large Language Models: Mitigating Cross-Task Interference in Multi-Task Instruct-Tuning
Short Chains, Deep Thoughts: Balancing Reasoning Efficiency and Intra-Segment Capability via Split-Merge Optimization
FIPN: Forward Self-Organizing Interpretable Polynomial Networks for Time Series Forecasting
Dismantling the Illusion of Vision-Language-Action Models Competence via Explicit Distributional Shifts
Reinforcement Learning from Bagged Reward
Manifold-Aware Perturbations for Constrained Generative Modeling
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
Position: LLMs Should Incorporate Explicit Mechanisms for Human Empathy
Positive–Unlabeled Reinforcement Learning Distillation for On-Premise Small Models
Complexity bounds for Dirichlet process slice samplers
Speedup Patch: Learning a Plug-and-Play Policy to Accelerate Embodied Manipulation
Semantic Tube Prediction: Beating LLM Data Efficiency with JEPA
RoboTwin 2.0: A Scalable Data Generator and Benchmark with Strong Domain Randomization for Robust Bimanual Robotic Manipulation
Memory-Efficient LLMs Training with Dynamic Sparsity: From Stability to Practical Scaling
Temporal Difference Learning for Diffusion Models
Unbiased Reward Modeling from Implicit Preference
AdaNav: Adaptive Reasoning with Uncertainty for Vision-Language Navigation
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
An Exterior Method for Nonnegative Matrix Factorization
Panini: Continual Learning in Token Space via Structured Memory
LoKiFormer: Locality-aware Attention with Decoupled Knowledge Memory for Efficient Large Language Model Pretraining
Learning Rate Scaling across LoRA Ranks and Transfer to Full Finetuning
A theory of learning data statistics in diffusion models, from easy to hard
Modeling Attributional Style at Scale: A Dataset and Analysis for Psychological Attribution Assessment and Reframing
Towards Practical World Model-based Reinforcement Learning for Vision-Language-Action Models
DAG-MoE: From Simple Mixture to Structural Aggregation in Mixture-of-Experts
RAPNet: Accelerating Algebraic Multigrid with Learned Sparse Corrections
Rate or Fate? RLV$^{\varepsilon}$R: Reinforcement Learning with Verifiable Noisy Rewards
Reinforcement Fine-Tuning Naturally Mitigates Forgetting in Continual Post-Training
Position: Uncertainty is a Strategic Signal in Human–AI Decision Making
Learning in Structured Stackelberg Games
Generative Adaptation of Dynamics to Environmental Shifts via Weight-space Diffusion
Revisiting the Bertrand Paradox via Equilibrium Analysis of No-regret Learners
Steal the Patch Size: Adversarially Manipulate Vision Language Models
Proteo-R1: Thinking Foundation Models for De Novo Protein Binder Design
Overcoming the Incentive Collapse Paradox
To Grok Grokking: Provable Grokking in Ridge Regression
Linear-Core Surrogates: Smooth Loss Functions with Linear Rates for Classification and Structured Prediction
Position: Hallucinations Undermine Trust; Metacognition is a Way Forward
Understanding Dynamics of Adam in Zero-Sum Games: An ODE Approach
Noisy Pairwise-Comparison Random Search for Smooth Nonconvex Optimization
Conformal Calibration Transfer
From Individual Calibration to Reliable Classifiers: ALD Parameterization with mPAIC Guarantees
Discovering Scaling Exponents with Physics-Informed Müntz-Szász Networks
Formalizing Learning from Language Feedback with Provable Guarantees
Estimating Correlation Clustering Cost in Node-Arrival Stream
Sinkhorn Treatment Effects
Benchmarking Agent Memory in Interdependent Multi-Session Agentic Tasks
Off-Policy Evaluation with Strategic Agents via Local Disclosure
On the Fragility of Data Attribution When Learning Is Distributed
Learning the ESG Geometry with Domain Aware Language Models
Gateways to Tractability for Satisfiability in Pearl’s Causal Hierarchy
Active Policy Optimization for Individualized Dosing via Gradient Variance Minimization
Powerful and Theoretically Guaranteed Independence Testing on Heterogeneous Federated Clients
Feasible Fusion: Constrained Joint Estimation under Structural Non-Overlap
Real-Time Visual Attribution Streaming in Thinking Model
A Noise Sensitivity Exponent Controls Large Statistical-to-Computational Gaps in Single- and Multi-Index Models
*Rank-Learner*: Orthogonal Ranking of Treatment Effects
Learning Reward–Cost Balance in Safe RL via Score-Based World Models
Normalizing Flows with Iterative Denoising
Detecting Perspective Shifts in Multi-Agent Systems
Large Scale Manifold Balanced Clustering
Physics in 2-Steps: Locking Motion Priors Before Visual Refinement Erases Them
Inducing LLM Workflows with Bilevel Optimization and Textual Gradients
Elastic Attention: Test-time Adaptive Sparsity Ratios for Efficient Transformers
Transformer Circuits Can Realize Clustering Algorithms
Parametrized Power-Iteration Clustering for Directed Graphs
Thoughtbubbles: an Unsupervised Method for Parallel Thinking in Latent Space
Dual-Calibration Multi-View Clustering via Compact Anchor Learning
Discretely-Refined Multi-view Clustering via Aligned Anchor Learning
Variable Clustering via Distributionally Robust Nodewise Regression
CURE: Consistency-under-Unified Semantic Regularization for Generalized Category Discovery
FasterVAR: Plug-and-Play Acceleration for Visual Autoregressive Models
On the existence of consistent adversarial attacks in high-dimensional linear classification
Polyphonia: Training-Free Context-Aware Music Editing 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
GRPO-based Cluster Decision Agent for Unknown-$\boldsymbol{K}$ Multi-view Clustering
MAGIC: Multi-Granularity Language-Informed Image Clustering
Beyond Independence: Learning Correlated Views for Variational Incomplete Multi-View Clustering
Nonconvex Low-Rank Tensor Representation with Deep Priors for Multiview Subspace Clustering
Bridging Functional and Representational Similarity via Usable Information
The Convergent Representation of Vision-Language Contrastive Learning: Geometry, Modality Gap and Shared Space Alignment
Timestep Rescheduling in Diffusion Inversion
PRISM: Synergizing Vision Foundation Models via Self-organized Expert Specialization
$f$-Divergence Self-Play for Tabular Anomaly Detection via Large Language Models
DeepBlip: Estimating Conditional Average Treatment Effects Over Time
Beyond Point Predictions: Manifold Expansion and Dual Alignment for Robust Time Series Distillation
Position: Every Ground Truth is a Human Construction, not an Objective Truth
Unfolded Laplacian Spectral Embedding: A Theoretically Grounded Approach to Dynamic Network Representation
Accurate Evaluation of Quickest Changepoint Detectors via Non-parametric Survival Analysis
Trifuse: Enhancing Attention-Based GUI Grounding via Multimodal Fusion
Branching Diffusion for Point Processes in Time and Space
ScenePilot: Controllable Boundary-Driven Critical Scenario Generation for Autonomous Driving
Power-Boosted Granger-Causal Discovery for Large Heterogeneous Panel Data
Learning to Extrapolate to New Tasks: A Relational Approach to Task Extrapolation
Automatic Unsupervised Ensemble Outlier Model Selection
Tuning-Free One-Class Discriminant Learning for Tabular Anomaly Detection
LRAgent: Efficient KV Cache Sharing for Multi-LoRA LLM Agents
SURF: Separation via Unsupervised Remixing Flow
SIMPC: Learning Self-Induced Mirror-Point Consistency for Unsupervised Point Cloud Denoising
One Coin Has Two Sides: Single Poistive Multi Label Learning from Salient Annotations
Beyond Global Alignment: Fine-Grained Motion-Language Retrieval via Pyramidal Shapley-Taylor Learning
Noise-Robust Density Estimation for Tabular Data Anomaly Detection
Position: Peer Review in ML/AI Conferences Should Separate Publication from Presentation and Offer Non-Anonymous Review Tracks
Error Propagation and Model Collapse in Diffusion Models: A Theoretical Study
Beyond Distribution Estimation: Simplex Anchored Structural Inference Towards Universal Semi-supervised Learning
SFedPO: Streaming Federated Learning with a Prediction Oracle under Temporal Shifts
On the Generalization in Topology Optimization via Sensitivity-Conditioned Bernoulli Flow Matching
Statistical Consistency and Generalization of Contrastive Representation Learning
Student-Centered Distillation Narrows the Agentic Gap Between Small and Large LLMs
Geometry-Aware Probabilistic Circuits via Voronoi Tessellations
Enhanced Multi-Instance Partial Label Learning via Average Gradient Outer Product
Semi-Supervised Learning with Noisy Covariates: Generalization Bounds and Distribution Regression
Compact Conformal Subgraphs
Learning-augmented Rent-or-Buy with a Sample
Generalizing Stochastic Smoothing for Differentiation and Gradient Estimation
Beyond Softmax: A Natural Parameterization for Categorical Random Variables
PyPop7: A Pure-Python Library for Population-Based Black-Box Optimization
Position: Zeroth-Order Optimization in Deep Learning Is Underexplored, Not Underpowered
Optimal Classical and Quantum Algorithms for 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
Position: Hippocampal Explicit Memory Is a Cornerstone to Human-Level AI
GHOST: Geometry-Guided Hallucination of Opaque Surface Textures
A Language-Guided Bayesian Optimization for Efficient LoRA Hyperparameter Search
A Graphop Analysis of Graph Neural Networks on Sparse Graphs: Generalization and Universal Approximation
Anytime-Valid Inference Under Outcome Delay: A Design-Based Approach
CurvZO: Adaptive Curvature-Guided Sparse Zeroth-Order Optimization for Efficient LLM Fine-Tuning
X-MoGe: A Cross-Modal Adaptation Framework with Mixture-of-Experts and Geometry Guidance for Heterogeneous Collaborative Perception
Taking the GP Out of the Loop
Finding Stationary Points by Comparisons
Fast and Scalable Analytical Diffusion
When More Data Doesn't Help: Limits of Adaptation in Multitask Learning
Regime-Adaptive Bayesian Optimization via Dirichlet Process Mixtures of Gaussian Processes
Speculative Coupled Decoding for Training-Free Lossless Acceleration of Autoregressive Visual Generation
Evolution Strategies at the Hyperscale
Unveiling the Entropy Dynamics of Chain-of-Thought Reasoning
Solving the Offline and Online Min-Max Problem of Non-smooth Submodular-Concave Functions: A Zeroth-Order Approach
$\texttt{MetaDistill}$: Unlocking the Performance Ceiling for Pretrained Optimizers
Replay Failures as Successes: Sample-Efficient Reinforcement Learning for Instruction Following
Revisiting Zeroth-Order Hessian Approximation: A Single-Step Policy Optimization Lens
Turning Stale Gradients into Stable Gradients: Coherent Coordinate Descent with Implicit Landscape Smoothing for Lightweight Zeroth-Order Optimization
Zeroth-Order Optimization at the Edge of Stability
Transformers Can Learn Posterior Predictive Distributions In-Context
$L^3$: Large Lookup Layers
Model-Preserving Adaptive Rounding
On the Epistemic Uncertainty of Overparametrized Neural Networks
BiSSL: Enhancing the Alignment Between Self-Supervised Pretraining and Downstream Fine-Tuning via Bilevel Optimization
Adaptive Group Elicitation via Multi-Turn LLM Interactions
Leveraging Low-Rank Structures for High-Dimensional Score-Based Sampling
Flow Sampling : Learning to Sample from Unnormalized Densities via Denoising Conditional Processes
Spectral Bridge Variational Inference: Dynamic LoRA via Bures-Wasserstein Gradient Flows
Set-Preserving Calibration from Conformal P-Values to E-Values
Probabilistic Retrofitting of Learned Simulators
Position: Evaluation of ML Resource Utilization Requires Model Life Cycle Assessment
Position: Enabling Fair Revenue Sharing for Data Providers in GenAI Systems
Position: AI Governance Needs ISO-like Interoperability Protocols, Not Just Laws
Incremental Learning of Sparse Attention Patterns in Transformers
Statistical Impossibility and Possibility of Aligning LLMs with Human Preferences: From Condorcet Paradox to Nash Equilibrium
Decoding Safety Feedback from Diverse Raters: A Data-driven Lens on Responsiveness to Severity
Differentially Private Preference Data Synthesis for Large Language Model Alignment
Near-Optimal Private Linear Regression via Iterative Hessian Mixing
Agentic Monte Carlo: Reinforcement Learning for Black-Box LLM Agents
Geometric Rate–Distortion Invariance for Domain Generalization
Toward Calibrated Mixture-of-Experts Under Distribution Shift
Phase-Type Variational Autoencoders for Heavy-Tailed Data
Density-Guided Continuous Flow for Robust Counterfactual Explanations
Emergence of Biased Consensus in Multi-Agent LLM Debates
Calibrating Conservatism for Scalable Oversight
Solving Spatial-Spectral Fusion with Latent Spectral Operators
State-Dependent Safety Failures in Multi-Turn Language Model Interaction
Decoy for the Judge: Disrupting Multi-Turn Jailbreaks using Semantics-Preserving Output Rewriting
Around the World in Eighty Ratings? Quantifying the Salience of Geo-Cultural Values for Pluralistic Alignment
GEM: Geometric Erasure by Contrastive Velocity Matching in Rectified Flows
When Benign Inputs Lead to Severe Harms: Eliciting Unsafe Unintended Behaviors of Computer-Use Agents
Autobidding Auctions with LLM-Powered Creatives
Generative Augmented Inference
BYORn: Bootstrap Your Own Responses to Defend Large Vision-Language Models Against Backdoor Attacks
DRPBench: Evaluating LLMs in Concurrent Code Comprehension via Fine-grained Data Race Prediction
Don't Walk the Line: Boundary Guidance for Filtered Generation
Cert-LAS: Toward Certified Model Ownership Verification for Text-to-Image Diffusion Models via Layer-Adaptive Smoothing
Spatial-Aware Reduction Framework: Towards Efficient and Faithful Visual State Space Models
MVI-Bench: A Comprehensive Benchmark for Evaluating Robustness to Misleading Visual Inputs in LVLMs
Multipole Semantic Attention: A Fast Approximation of Softmax Attention for Pretraining
Left–Right Symmetry Breaking in CLIP-style Vision-Language Models Trained on Synthetic Spatial-Relation Data
DFSAttn: Dynamic Fine-grained Sparse Attention for Efficient Video Generation
AutoWebWorld: Synthesizing Infinite Verifiable Web Environments via Finite State Machines
Robust Filter Attention: Self-Attention as a Parallel State Estimator
Universal Approximation with Softmax Attention
Test-Time Training Is Secretly Linear Attention
You Need Better Attention Priors
Anatomy of Massive Activations and Attention Sinks
Quaternion Self-Attention with Shared Scores
Linearizing Vision Transformer with Test-Time Training
Revisiting Pre-Propagation GNNs: Robust Diffusion Operators and Hidden-State Re-Propagation
A novel statistical approach to analyze image classification
ACO-MoE-LoRA: Evolving-while-Training for Adapting Segment Anything Model 2 to Specialized Domains
CoLA: Cross-Modal Low-rank Adaptation for Multimodal Downstream Tasks
Structured Diffusion Bridges: Inductive Bias for Denoising Diffusion Bridges
Mitigating Label Shift in Tabular In-Context Learning via Test-Time Posterior Adjustment
Similarity Is Not Logic: Factored Inference for Dual-Encoder Vision-Language Models
Diversity Matters: Revisiting Test-Time Compute in Vision-Language Models
MEDA: Medical-Oriented Activation Editing for Hallucination Mitigation in Medical Large Vision-Language Model
Stabilizing MoE Reinforcement Learning by Aligning Training and Inference Routers
ChaosNexus: A Foundation Model for ODE-based Chaotic System Forecasting with Hierarchical Multi-scale Awareness
Head-in-Head in Linear Attention
Ramba: Selective State-Space Models for Relational Deep Learning
Position: the Stochastic Parrot in the Coal Mine. Model Collapse is a Threat to Low-Resource Communities
From Observations to States: Latent Time Series Forecasting
MODUS: Decoder-only Any-to-Any Modeling of Diverse Modalities
Inverse Entropic Optimal Transport Solves Semi-supervised Learning via Data Likelihood Maximization
Efficient Synthetic Network Generation via Latent Embedding Reconstruction
Riemannian stochastic optimization for sufficient dimension reduction
PINNfluence: Interpreting PINNs through Influence Functions
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
RLSF-V: Mitigating Hallucinations in MLLMs via Fuzzy Semantic Self-Feedback
SE(3)-Equivariant Flow Matching with Gaussian Process Priors for Geometric Trajectory Prediction
Geometry-Aware Tabular Diffusion
Model-Dowser: Data-Free Importance Probing to Mitigate Catastrophic Forgetting in Multimodal Large Language Models
Triadic Dynamics Aware Diffusion Posterior Sampling for Inverse Problems: Optimizing Guidance and Stochasticity Schedules
Geometric Decoupling: Diagnosing the Structural Instability of Latent
Breaking the Simplification Bottleneck in Amortized Neural Symbolic Regression
FourTune: Towards Fully 4-Bit Efficient Post-Training for Diffusion Models
Solving Positive Linear Programs with Differential Privacy
Efficient Diffusion LLMs via Temporal-Spatial Parallel Decoding and Confidence Extrapolation
Watch Your Step: Information Injection in Diffusion Models via Shadow Timestep Embedding
Scalable GANs with Transformers
Neural Dispersion on Graphs
Riemannian Neural Optimal Transport
PointDiT: Pixel-Space Diffusion for Monocular Geometry Estimation
LIVE: Long-horizon Interactive Video World Modeling
Chamaileon: Cross-Context Binder Design with Contextualized Modeling and Mixed Sampling
SGMD: Score Gradient Matching Distillation for Few-Step Video Diffusion Distillation
Induction Heads Interpolate N-Grams
Trajectory-Aware Spiking DiTs Conversion via Membrane Potential Error-Feedback
Geometry-Correct Diffusion Posterior Sampling with Denoiser-Pullback Curvature Guidance and Manifold-Aligned Damping
Tail Annealing for Heavy-Tailed Flow Matching
The Lie We Tell: Correcting the Euclidean Fallacy in Vision Language Action Policies via Score Matching on Tangent Space
GraphP-FL: Personalized Federated Graph Learning via Dynamic Structure Awareness and Fisher Information Elastic Alignment
Learnable Kernel Density Estimation for Graphs and Its Application to Graph-Level Anomaly Detection
End-to-end Graph-structured Brain Representation Learning
Rethinking Efficient Graph Coarsening via a Non-Selfishness Principle
Uncertainty-Constrained Trustworthiness for Graph Learning
Entangled No More: Multi-Domain Decoupling for Robust Dynamic Graph Neural Networks
Anchor-guided Hypergraph Condensation with Dual-level Discrimination
A Pure Hierarchical Spectral Parcellation Network for Brain Network Analysis
VDW-GNNs: Vector diffusion wavelets for geometric graph neural networks
Quantile-Free Uncertainty Quantification in Graph Neural Networks
SoMA: A Real-to-Sim Neural Simulator for Robotic Soft-Body Manipulation
Alternating Reinforcement Learning for Rubric-Based Reward Modeling in Non-Verifiable LLM Post-Training
GraphFlow: A Graph-Based Workflow Management for Efficient LLM-Agent Serving
Beyond Scalar Rewards: Learning from Text Feedback in LLM Post-Training
InnoEval: On Research Idea Evaluation as a Knowledge-Grounded, Multi-Perspective Reasoning Problem
Batched Contextual Reinforcement
ToMAP: Training Opponent-Aware LLM Persuaders with Theory of Mind
Hierarchical Goal Abstractions via Learned Subset Relations
ActiveUltraFeedback: Efficient Preference Data Generation using Active Learning
Hallucination Detection from Structural Reasoning Model
Schur-A*: Layer-wise Optimal Expert Pruning for Sparse MoEs via Schur-Complement Guided A* Search
Learning Manifold and Itô Dynamics with Branched Neural Rough Differential Equations
EpiCache: Episodic KV Cache Management for Long-Term Conversation on Resource-Constrained Environments
E-mem: Multi-Agent Based Episodic Context Reconstruction for LLM Agent Memory
SSL4RL: Revisiting Self-supervised Learning as Intrinsic Reward for Visual-Language Reasoning
S-Quant: Rethinking Weight Quantization with Seed-Based Generation
How Few-Shot Examples Add Up: A Causal Decomposition of Function Vectors in In-Context Learning
DOUBT: Decoupled Object-level Understanding and Bridging via vMF-based Trustworthiness for Hallucination Detection in MLLMs
Efficient Reasoning with Hidden Thinking
Connecting Independently Trained Modes via Layer-Wise Connectivity
Can LLM Agents Stick to the Script? Modeling Commitment in Interactive Narratives
IRPM: Intergroup Relative Preference Modeling for Pointwise Generative Reward Models
Utility-Diversity Aware Online Batch Selection for LLM Supervised Fine-tuning
Welfare-Optimal Classification with Accuracy Auctions
BandPO: Bridging Trust Regions and Ratio Clipping via Probability-Aware Bounds for LLM Reinforcement Learning
PostTrainBench: Can LLM Agents Automate LLM Post-Training?
Unlearning’s Blind Spots: Over‑Unlearning and Prototypical Relearning Attack
SPARC: Separating Perception And Reasoning Circuits for Test-time Scaling of VLMs
SSDCN: Spatial-Spectral Dual-Clustering-based Network for Hyperspectral Image Super-resolution
Representation Learning for Equivariant Inference with Guarantees
Trust Region Masking for Long-Horizon LLM Reinforcement Learning
Certain Head, Uncertain Tail: Expert-Sample for Test-Time Scaling in Fine-Grained MoE
What Does Vision Tool-Use Reinforcement Learning Really Learn? Disentangling Tool-Induced and Intrinsic Effects for Crop-and-Zoom
Plug-and-Play Spiking Operators: Breaking the Nonlinearity Bottleneck in Spiking Transformers
Beyond Perplexity: UTF-8 Validity in Byte-aware Language Models
Compute When Worth It: Risk Control for Reasoning on a Compute Budget
Generative Visual Code Mobile World Models
STT-LLM: Structural-Temporal Tokenization for Adapting LLMs to Longitudinal Clinical Profiles
PatternKV: Flattening KV Representation Expands Quantization Headroom
MathlibLemma: Folklore Lemma Generation and Benchmark for Formal Mathematics
Pushing Forward Pareto Frontiers of Proactive Agents with Behavioral Agentic Optimization
Offline Two-Player Zero-Sum Markov Games with KL Regularization
ReSpinQuant: Efficient Layer-Wise LLM Quantization via Subspace Residual Rotation Approximation
AdverMCTS: Combating Pseudo-Correctness in Code Generation via Adversarial Monte Carlo Tree Search
Zero-source LLM Hallucination Detection with Human-like Criteria Probing
Anytime Safe PAC Efficient Reasoning
HiPhO: How Far Are (M)LLMs from Humans in the Latest High School Physics Olympiad Benchmark?
Symbol-Equivariant Recurrent Reasoning Models
GeoDM: Geometry-aware Distribution Matching for Dataset Distillation
Skip-It? Theoretical Conditions for Layer Skipping in Vision–Language Models
Intrinsic Task Symmetry Drives Generalization in Algorithmic Tasks
MuonSSM: Orthogonalizing State Space Models for Sequence Modeling
Learning Coherent Representations: A Topological Approach to Interpretability
Controlled Dynamics Attractor Transformer
Learning Attribute–Affordance Hierarchies in Hyperbolic Space for Open-Vocabulary 3D Object Affordance Grounding
On the Relationship Between Activation Outliers and Feature Death in Sparse Autoencoders
Robust Reinforcement Learning in a Sample-Efficient Setting
Mirror Descent Under Generalized Smoothness
Aligning Datasets and Models for Weight Space Learning
Activation with Intrinsic-Extrinsic Consensus
Controlling the Risk of Corrupted Contexts for Language Models via Early-Exiting
Plain Transformers are Surprisingly Powerful Link Predictors
Intra-Modal Neighbors Never Lie: Rectifying Inter-Modal Noisy Correspondence via Graph-Based Intra-Modal Reasoning
Self-Calibrated Consistency can Fight Back for Adversarial Robustness in Vision-Language Models
Stable Spectral Copula Alignment for Robust Multimodal Learning
Submodular Optimization for Minimal Augmentation in Robust Language Model Alignment
SS‑TPT: Stability and Suitability-Guided Test-Time Prompt Tuning for Adversarially Robust Vision-Language Models
Geometrically Constrained Outlier Synthesis
Error-Driven Graph Augmentation for Mesh-Based PDE Surrogates
DDGA: Dirichlet Distributional Gradient Aggregation for Transferable Vision-Language Adversarial Attacks
Emergent Biological Realism in RL-Trained DNA Language 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
Unbiased and Second-Order-Free Training for High-Dimensional PDEs
CURVE: Learning Causality-Inspired Invariant Representations for Robust Scene Understanding via Uncertainty-Guided Regularization
rePIRL: Learn PRM with Inverse RL for LLM Reasoning
Discovering Ordinary Differential Equations with LLM-Based Qualitative and Quantitative Evaluation
On the Adversarial Robustness of Large Vision-Language Models under Visual Token Compression
With Argus Eyes: Assessing Retrieval Gaps via Uncertainty Scoring to Detect and Remedy Retrieval Blind Spots
DiL: Discrete-anchored Representation Alignment for Semi-Supervised Continual Learning
Ellipsoidal Time Series Forecasting
DECOR: Learning to Decompose and Collaborate in Deep Search via Multi-Agent Reinforcement Learning
Continuous-Time Piecewise-Linear Recurrent Neural Networks
TokenRatio: Principled Token-Level Preference Optimization via Ratio Matching
Towards Foundation Models for Zero-Shot Time Series Anomaly Detection: Leveraging Synthetic Data and Relative Context Discrepancy
Mitigating the Modality Gap in Vision–Language Models with Fractal Spectral Geometry
Segmentation From Attention: Training-Free Layer Selection and One-Shot Tuning for Segmentation in VLMs
Provable Bounds for the Learnability of Sample-Compressible Families from Noisy Samples
TIMI: Training-Free Image-to-3D Multi-Instance Generation with Spatial Fidelity
Phy-CoSF: Physics-Guided Continuous Spectral Fields Reconstruction and Spectral Super-Resolution for Snapshot Compressive Imaging
PRISM: Training-Free Video Anomaly Detection via Intrinsic Statistical Modeling
Task-Aware Preference Calibration for Direct Preference Optimization
SceneDirector: Bridging Explicit Geometry and Generative Priors for Unified Driving Scene Editing
A Hypertoroidal Covering for Perfect Color Equivariance
VideoBrain: Learning Adaptive Frame Sampling for Long Video Understanding
CRAG: Can 3D Generative Models Help 3D Assembly?
OcclusionFormer: Arranging Z-Order for Layout-Grounded Image Generation
What Makes Synthetic Data Effective in Image Segmentation
STARCaster: Spatio-Temporal AutoRegressive Video Diffusion for Identity- and View-Aware Talking Portraits
RADIO1D: Elastic Representations for Condensed Vision Modeling
Glimpse: Geometry Learning of Multi-scale Structural Priors for 3D Pose Estimation
AVTrack: Audio-Visual Speaker Tracking in Complex Scenes
Disentangling Consensus and Value-Specific Representations for Controllable Pluralistic Value Alignment of LLMs
DEGAP: Dynamic Entropy-Guided Attention Perturbation for Contrastive Decoding in Large Vision-Language Models
Motion Dynamics Learning for Few-Shot Embodied Adaptation
Crowd4D: Scene-Aware Monocular 4D Crowd Reconstruction
Adversarial Vulnerability from Interference Between Features in Superposition
Beyond Detection: A Structure-Aware Framework for Scene Text Tracking
DRFusion: Drift-Resilient Temporally Consistent Infrared–Visible Video Fusion
When Preference Labels Fall Short: Aligning Diffusion Models from Real Data
Fine-grained Analysis of Brain-LLM Alignment through Input Attribution
Kinematics-Driven Gaussian Shape Deformation for Blurry Monocular Dynamic Scenes
Geometric Collapse: When Vision Models Fail to Verify Physical Causality
Geometric Reciprocity: Unlocking Self-Supervision for Stereoscopic Video Generation
Localized, High-resolution Geographic Representations with Slepian Functions
WorldComp2D: Spatio-semantic Representations of Object Identity and Location from Local Views
RobuQ: Pushing DiTs to W1.58A2 via Robust Activation Quantization
Learning Stochastic Bridges for Video Object Removal via Video-to-Video Translation
EPS3D: End-to-End Feed-Forward 3D Panoptic Segmentation
Scale-Aware Domain Harmonization for Domain Adaptation Person Search
Native Spatio-Temporal 4D Variational Autoencoder
De-Linearizing Agent Traces: Bayesian Inference of Latent Partial Orders for Efficient Execution
WildActor: Unconstrained Identity-Preserving Video Generation
AgentXRay: White-Boxing Agentic Systems via Workflow Reconstruction
Physics-informed Neural Operator Learning for Nonlinear Grad-Shafranov Equation
Identifiable Markov Switching Models with Instantaneous Effects and Exponential Families
What Makes a Good Representation for Single-Cell Perturbation Prediction?
Flow-Based Density Ratio Estimation for Intractable Distributions with Applications in Genomics
CryoACE: An Atom-centric Framework for Accurate and Automated Model Building in Cryo-EM
Lagrangian Perturbation Diffusion Steering: Latent Reinforcement Learning for Generative Policies
Geometric Convergence of Gauss–Newton for Neural Networks: Riemannian Geometry and Adaptive Damping
GenAlign: Towards Unified Alignment Framework of MLLMs via Generative Reward Model
MADA-Attack: Transferable Multi-modal Attention Distraction Adversarial Attack against Vision Language Models
Marrying Generative Model of Healthcare Events with Digital Twin of Human-Environment Interaction for Disease Reasoning
On Revisiting Entropy for Identifying Mislabeled Medical Images
Listening Through the Noise: Cauchy-Driven Diffusion Bridges for Robust Gastrointestinal Auscultation and Clinical Benchmarking
Seizure-Semiology-Suite($S^3$): A Clinically Multimodal Dataset, Benchmark, and Models for Seizure Semiology Understanding
SpaEF: Spatially Resolved Transcriptomics Data Element-Wise Denoising Framework Powered by Large Models
DPsurv: Dual-Prototype Evidential Fusion for Uncertainty-Aware and Interpretable Whole Slide Image Survival Prediction
From Token to Token Pair: Efficient Prompt Compression for Large Language Models in Clinical Prediction
HEXST: Hexagonal Shifted-Window Transformer for Spatial Transcriptomics Gene Expression Prediction
SwitchCraft: Programmatic Design of State-Switching Proteins
Long-Horizon Model-Based Offline Reinforcement Learning Without Conservatism
Inverting Data Transformations via Diffusion Sampling
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
Cardio-mmFlow: A Gaussian-Prior-Free Physics-Informed Flow Matching Framework for Electrocardiogram to mmWave Radar Synthesis.
How (Not) to Hybridize Neural and Mechanistic Models for Epidemiological Forecasting
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
AG-REPA: Causal Layer Selection for Representation Alignment in Audio Flow Matching
A Theory of Contrastive Learning with Natural Images
Stream RAG: Instant and Accurate Spoken Dialogue Systems with Streaming Tool Usage
Ranking Free RAG: Replacing Re-ranking with Selection in RAG for Sensitive Domains
Breaking the Reference Bottleneck via Learning to Rewrite Conversational Queries without Gold Reference Passages
AuTAgent: A Reinforcement Learning Framework for Tool-Augmented Audio Reasoning
ReGen: Hierarchical Multi-Prompt Representation Generation for Efficient Waveform Diffusion Models
The Silent Thought: Modeling Internal Cognition in Full-Duplex Spoken Dialogue Models via Latent Reasoning
Backjump-on-Graph: Empowering LLMs with Reinforced Retrospective Exploration for Agentic KG Reasoning
A Semantically Consistent Dataset for Data-Efficient Query-Based Universal Sound Separation
EmBrace: A Collective Knowledge Fusion Framework Toward Unified EEG Foundation Models
Towards Generalizable EEG-to-fMRI Synthesis via a Unified, Context-Aware Prompting Framework
PATCHCODE: Discrete Latent Predictive Learning for EEG Foundation Model
Characterizing the Predictive Impact of Modalities with Supervised Latent-Variable Modeling
Learning to Route Languages for Multilingual Preference Optimization
Efficient Distributionally Robust Assortment Optimization in MNL Bandits
Toward Culturally Aligned LLMs through Ontology-Guided Multi-Agent Reasoning
FOVI: A biologically-inspired foveated interface for deep vision models
AutoMoT: A Unified Vision-Language-Action Model with Asynchronous Mixture -of-Transformers for End-to-End Autonomous Driving
Transport or Discard: Robust Unbalanced Optimal Transport for Cross-Domain Policy Adaptation
Temporal Context Reinstatement Drives Episodic-Like Order Memory in Long-Context Language Models
EEG-FM-Bench: A Comprehensive Benchmark for the Systematic Evaluation and Diagnostic Analyses of EEG Foundation Models
Bridging the Gap in Autonomous Science: The Corpus and Benchmark for Biological Protocol Reasoning
Not All Frequencies Are Equal: Energy-Adaptive Diffusion for Time Series Forecasting
ZeroDiff: Zero-Shot Time Series Reconstruction via Informed-Prior Diffusion
It's TIME: Towards the Next Generation of Time Series Forecasting Benchmarks
Noisy-Space Policy Gradient for Diffusion Policies in Offline Reinforcement Learning
TopoDistill: Distilling Global System Topology for Causal Discovery in Multivariate Time Series
ADHD Disease Detection Based on Short- and Long-Term Brain Function Encoding and Memory Graph Network
Dynamic TMoE: A Drift-Aware Dynamic Mixture of Experts Framework for Non-Stationary Time Series Forecasting
ConTSG-Bench: A Unified Benchmark for Conditional Time Series Generation
Holi-Spatial: Evolving Video Streams into Holistic 3D Spatial Intelligence
Time-Series Decomposition as a standalone Task: A Mechanism-Driven Diagnostic Benchmark
Revealing Scaling Behavior in Large-scale Time Series Models: Implications for More Efficient and Accurate Forecasting
Shapley Regularized Neural Granger Causality
Incremental Transformer Neural Processes
Learning Fingerprints for Medical Time Series with Redundancy-Constrained Information Maximization
TelecomTS: A Multi-Modal Observability Dataset for Time Series and Language Analysis
Copyright-Bench: Agentic Evaluation of Copyright Law Compliance
TeamWork: Multivariate Time Series Anomaly Detection via Asymmetric Role-aware Channel Modeling
Sonar-TS: Search-Then-Verify Natural Language Querying for Time Series Databases
Nested Spatio-Temporal Time Series Forecasting
AutoVSR: Automatic Visual-to-Symbolic Reasoning for Symbolic Expression Generation from Circuit Schematic
RulePlanner: All-in-One Reinforcement Learner for Unifying Design Rules in 3D Floorplanning
HyperMLP: An Integrated Perspective for Sequence Modeling
Large-Scale Notification Dispatch with Bundle Treatments and Multi-Outcome Uplift Optimization
Physically-Guided Data-Space Rectified Flow for Precipitation Nowcasting
Blending Neural Control Density Functions for Stabilization and Safety
GIFT: Bootstrapping Image-to-CAD Program Synthesis via Geometric Feedback
PerceptOS: Semantic-Aware Kernel Optimization for OS-Intensive Workloads via Hardware-Software Alignment
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
AutoNumerics-Zero: Automated Discovery of State-of-the-Art Mathematical Functions
BiTrajDiff: Bidirectional Trajectory Generation with Diffusion Models for Offline Reinforcement Learning
SEAgent: Self-Evolving Computer Use Agent with Autonomous Learning from Experience
Achieving Logarithmic Regret in KL-Regularized Zero-Sum Markov Games
Provably Convergent Actor-Critic in Risk-averse MARL
Comparing Deterministic and Soft Policy Gradients for Optimizing Gaussian Mixture Actors
Online Rubrics Elicitation from Pairwise Comparisons
Video-Based Optimal Transport for Feedback-Efficient Offline Preference-Based Reinforcement Learning
Position: Make Planning Research Rigorous Again!
DeltaEvolve: Accelerating Scientific Discovery through Momentum-Driven Evolution
Learning Latent Action World Models In The Wild
Fast and Highly Expressive Policy Learning for Offline Reinforcement Learning via Bootstrapped Flow Q-Learning
Beyond Static Pipelines: Learning Dynamic Workflows for Text-to-SQL
Spectral–Spatial Mixing with Morphology-Aware Adaptive Loss for Medical Image Segmentation.
B-Spar: Bayesian Sparse-Reward Modeling for RL-based Image Editing
Episodic Memory-Guided Controllable Experience Synthesis for Reinforcement Learning
Decision-Focused Learning via Tangent-Space Projection of Prediction Error
GRASP: Graph Reasoning via Agentic Solving and Probing of LLMs
Mitigating Plasticity Loss through Architectural Design in Continual Learning
TimeAutoDiff: A Unified Framework for Generation, Imputation, Forecasting, and Time-Varying Metadata Conditioning of Heterogeneous Time Series Tabular Data
Seeing the Unseen: Physics-as-Representation for Generalizable Gaze Perception
When RL Meets Adaptive Speculative Training: A Unified Training-Serving System
Expo-GS: Exposure-Aware Signed Distance Function in Gaussian Splatting for High Dynamic Range
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
ExSkill: Continual Learning from Experience and Skills in Multimodal Agents
FS-I2P: A Hierarchical Focus–Sweep Registration Network with Dynamically Allocated Depth
EquiCAD: A Geometric Equivariant Neural Network for 3D Shape Classification
RubricRobustness: A Simple Framework for Evaluating the Robustness of Rubrics-Based Benchmarks
TN-SHAP-G: Graph-Structured Tensor Network Surrogates for Shapley Values and Interactions
Beyond Test-Time Training: Learning to Reason via Hardware-Efficient Optimal Control
Efficient Transformer Attention for SNNs via Hadamard Simplification
$V_0$: A Generalist Value Model for Any Policy at State Zero
ECHO: Entropy-Confidence Hybrid Optimization for Test-Time Reinforcement Learning
ExpertWeaver: Unlocking the Inherent MoE in Dense LLMs with GLU Activation Patterns
SparseOpt: Addressing Normalization-induced Gradient Skew in Sparse Training
ECO: Quantized Training without Full-Precision Master Weights
Hyperbolic Multimodal Continual Learning
Contribution Weights: A Geometrical Analysis of Self-Attention Transformers
Graph Neural Dynamics via Learned Energy and Tangential Flows
Barriers to Counterfactual Credit Attribution for Autoregressive Models
Who Transfers Safety? Identifying and Targeting Cross-Lingual Shared Safety Neurons
Condition Number Based Low-Bit Quantization for Image Super-Resolution
Quant VideoGen: Auto-Regressive Long Video Generation via 2-Bit KV-Cache Quantization
OSF: On Pre-training and Scaling of Sleep Foundation Models
A Unified Framework for Deep Hypergraph Clustering Beyond Homophily
Guaranteed Optimal Compositional Explanations for Neurons
Model Monotonicity in Autobidding Auctions: When Do Better Predictions Lead to Better Outcomes?
FormalJudge: A Neuro-Symbolic Paradigm for Agentic Oversight
Memory is Reconstructed, Not Retrieved: Graph Memory for LLM Agents
Theoretical Guarantees for One-Shot Magnitude Pruning and Compute-Adaptive Early Exit
A Direct Second-Order Method for Solving Two-Player Zero-Sum Games
Understanding Generalization and Forgetting in In-Context Continual Learning
TRAP: Hijacking VLA CoT-Reasoning via Adversarial Patches
Provably Data-driven Lagrangian Relaxation for Mixed Integer Linear Programming
Regularized Discriminative Alignment for Deep Representations under Label Shift
Bilinear Bandits with Partially Observable Features
How Chain of Thought Decomposes Complex Tasks
Follow-the-Perturbed-Leader for Decoupled Bandits: Best-of-Both-Worlds and Practicality
FeRA: Frequency-Energy Constrained Routing for Effective Diffusion Adaptation Fine-Tuning
Accelerated and Stable Convergence with Anchored Generalized Optimistic Method
Particles Don’t Care About Z: Towards Scaling Entropy Estimation of Unnormalized Densities
Mirror Mean-Field Langevin Dynamics
Benchmarking the Limits of In-Context Reinforcement Learning for Ad-Hoc Teamwork
New Bounds for Kernel Sums via Fast Spherical Embeddings
Learning Discrete Diffusion on Graphs via Free-Energy Gradient Flows
Leveraging Gauge Freedom for Learning Non-Gradient Population Dynamics of Stochastic Systems
dnaHNet: A Scalable and Hierarchical Foundation Model for Genomic Sequence Learning
Search Space Synthesis for Parametric Functions
Is Spurious Correlation Removal Always Learnable?
Quantum Algorithms for Triangle Cut Sparsification
Causal Modeling of Selection in Evolution
An Evidential Route to Asymptotic Bayes Optimality under Sparsity
CSOR: Coreset Selection for Object Re-identification via Class Pruning
Persona2Web: Benchmarking Personalized Web Agents for Contextual Reasoning with User History
Position: Improved Documentation is Necessary for Benchmarking AI Systems in Geometry
Position: Fairness Failure in Generative Models is an Evaluation Problem
Position: Agent Evaluation Should Be Agentified for Openness, Standardization, and Reproducibility
CentaurEval: Benchmarking Human-in-the-Loop Value in Agentic Coding
Rapid Poison: Practical Poisoning Attacks Against the Rapid Response Framework
DEER: A Benchmark for Evaluating Deep Research Agents on Expert Report Generation
Return-Aligned Decision Transformer
Estimating Tail Risks in Language Model Output Distributions
See More, Forecast Better and Faster: Enhancing Time Series Foundation Models via Inference-Time Plug-and-Play Downsampling
Do Text Edits Generalize to Visual Generation? Benchmarking Cross-Modal Knowledge Editing in UMMs
Reasoning to Edit: Hypothetical Instruction-Based Image Editing with Visual Reasoning
Leaderboard Incentives: Model Rankings under Strategic Post-Training
Estimating the Empowerment of Language Model Agents
Rethinking Video Generation Model for the Embodied World
CLAM-Bench: Benchmarking LLM Agents for Library-Scale Cross-Architecture Migration
Collaborative likelihood-ratio estimation over graphs
Bipartite Graph Attention-based Clustering for Large-scale scRNA-seq Data
Position: Quantum Kernel Machines Should Move Beyond Scalar-Valued Kernels to Realize Their Potential
Compositional Perception and Generalizing Induction: Latent Compositional Manifold Assumption on Generalized Category Discovery
Rethinking Loss Reweighting for Imbalance Learning as an Inverse Problem: A Neural Collapse Point of View
LEMUR: Learned Multi-Vector Retrieval
FedRot-LoRA: Mitigating Rotational Misalignment in Federated LoRA
PhysForge: Generating Physics-Grounded 3D Assets for Interactive Virtual World
Cost-aware Stopping for Bayesian Optimization
Beyond Hamming: Query-Aware Decoding of Binary Cosine Sketches
AReaL-DTA: Dynamic Tree Attention for Efficient Reinforcement Learning of Large Language Models
FloorplanQA: A Benchmark for Spatial Reasoning in LLMs using Structured Representations
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?
Less Is More in Federated Continual Learning: RieSelect for Conflict-Aware Layer Selection in LLMs
MoCL: Metabolic Optimization for Curvature-Aware Continual Learning
Dynamic Optimizations of LLM Ensembles with Two-Stage Reinforcement Learning Agents
Are Large Reasoning Models Interruptible?
Efficient Bilevel Optimization for CKA-Guided MoE Upcycling
Shapley Neuron Values for Continual Learning: Which Neurons Matter Most?
Feature Collapse Under Corruption: An Entropy Perspective on Robust Neural Networks
Mixing Expertise with Confidence: A Mixture of Expert Framework for Robust Multi-Modal Continual Learner
CARD: Coarse-to-fine Autoregressive Modeling with Radix-based Decomposition for Transferable Free Energy Estimation
Segment Anything with Robust Uncertainty-Accuracy Correlation
Federated Learning with Unlabeled Clients: Personalization Can Happen in Low Dimensions
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
ViSurf: Visual Supervised-and-Reinforcement Fine-Tuning for Large Vision-and-Language Models
Controlled Collaboration Geometry for Personalized Federated Learning
A Geometry-Aware Efficient Algorithm for Compositional Entropic Risk Minimization
Operator Splitting with Hamilton-Jacobi-based Proximals
Improved Dynamic Algorithm for Non-monotone Submodular Maximization under Cardinality Constraint
Hölder++: Improving Quality-Coherence Trade-off in Multimodal VAEs
Reinforcement Learning from Human Feedback with Active Queries
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
LoBCD-GW: A Fast and Data-Dependent Algorithm for Computing Gromov-Wasserstein Distance via Localized Block Coordinate Descent
Robust Contextual Optimization with Missing Covariates
General Analysis of LMO-based Optimizers: Beyond Bounded Variance
Towards Fully Parameter-Free Stochastic Optimization: Grid Search with Self-Bounding Analysis
OVLR: Efficient, Scalable, and Robust Training via Output-Level Variance-Reduced Likelihood Ratio
An Embarrasingly Simple Way to Optimize Orthogonal Matrices at Scale
OPT-Engine: Benchmarking the Limits of LLMs in Optimization Modeling via Complexity Scaling
Position: Code Benchmarks Should Prioritize Rigor, Reliability, and Reproducibility
Mixture of Concept Bottleneck Experts
WMVLM: Evaluating Diffusion Model Image Watermarking via Vision-Language Models
SurrogateSHAP: Training-Free Contributor Attribution for Text-to-Image (T2I) Models
Ariadne's Thread of LipSync: Unraveling Forgeries via Inconsistency between Lip Motions and Head Poses
Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants
Fair Dataset Distillation via Cross-Group Barycenter Alignment
Spectral Guidance for Flexible and Efficient Control of Diffusion Models
COPF: An Online Framework for Deployment-Stable Counterfactual Fairness in Evolving Graphs
Extending Fair Null-Space Projections for Continuous Attributes to Kernel Methods
When Do Diffusion Models learn to Generate Multiple Objects?
Demystifying the Optimal Fair Classifier in Multi-Class Classification
Fairness in Aggregation: Optimal Top-$k$ and Improved Full Ranking
A Game-Theoretic Framework for Measuring and Explaining Metric Compatibility in Fair Machine Learning
StretchTime: Adaptive Time Series Forecasting via Symplectic Attention
FairRARI: A Plug and Play Framework for Fairness-Aware PageRank
Beyond Model Ranking: Predictability-Aligned Evaluation for Time Series Forecasting
Test-Time Debiasing with Probabilistic Prompts via Wasserstein Distance in Vision-Language Models
INFER: Learning Implicit Neural Frequency Response Fields for Confined Acoustic Environments
Prompt Reinjection: Alleviating Prompt Forgetting in Multimodal Diffusion Transformers
What Language is This? Ask Your Tokenizer.
Beyond Procedure: Substantive Fairness in Conformal Prediction
Conf-Gen: Conformal Uncertainty Quantification for Generative Models
Optimal Transport under Group Fairness Constraints
MAFE: Enabling Equitable Algorithm Design in Multi-Agent Multi-Stage Decision-Making Systems
Preserving Expert-Level Privacy in Offline Reinforcement Learning
SIGMA-PPG: Statistical-prior Informed Generative Masking Architecture for PPG Foundation Model
Differentially Private and Scalable Estimation of the Network Principal Component
Neural QAOA$^2$: Differentiable Joint Graph Partitioning and Parameter Initialization for Quantum Combinatorial Optimization
FedHPro: Federated Hyper-Prototype Learning via Gradient Matching
Trajectory-Aware Certified Decentralized Unlearning via SGD Stability
Homophily-Heterogeneity Gradient Surgery for Federated Graph Learning
Accuracy-First Rényi Differential Privacy and Post-Processing Immunity
EAGer: Entropy-Aware GEneRation for Adaptive Inference-Time Scaling
Deformba: Vision State Space Model with Adaptive State Fusion
Eliminating Solution Bias in Differentially Private Optimization
OSNIP: Breaking the Privacy-Utility-Efficiency Trilemma in LLM Inference via Obfuscated Semantic Null Space
Efficient DP-SGD for LLMs with Randomized Clipping
Shuffling-Aware Optimization for Private Vector Mean Estimation
MotiMotion: Motion-Controlled Video Generation with Visual Reasoning
Efficient Public Verification of Private ML via Regularization
MORE: A Multilingual Document Parsing Benchmark and Evaluation
Finding Differentially Private Second Order Stationary Points in Stochastic Minimax Optimization
Multi-Scale Wavelet Transformers for Operator Learning of Dynamical Systems
ACTG-ARL: Differentially Private Conditional Text Generation with RL-Boosted Control
GAUSS: Graph-Assisted Uncertainty Quantification using Structure and Semantics for Long-Form Generation in LLMs
Understanding and Mitigating Token-Pruning-Induced Vulnerabilities in VLMs
Erased but Not Forgotten: How Backdoors Compromise Concept Erasure
Adversarial Robustness of Implicit Neural Representation-Based Classifiers
Internalizing Safety Understanding in Large Reasoning Models via Verification
DF-LoGiT: Data-Free Logic-Gated Backdoor Attacks in Vision Transformers
Neural Honeytrace: Plug&Play Watermarking Framework against Model Extraction Attacks
CircuitPrint: Mechanistic Circuit Fingerprints for Large Language Models
LEGO-FL: Learning Heterogeneous Federated Models as a LEGO Assembly Games
Optimized Deferral for Imbalanced Settings
Graph-Preference Learning: Debiasing Network-Sampled Human Feedback for Target Welfare Estimation
Reinforcement Learning via Self-Distillation
Keep It in Mind: User Centric Continual Spatial Intelligence Reasoning in Egocentric Video Streams
MM-DeepResearch: A Simple and Effective Multimodal Agentic Search Baseline
AD-BTS: Adaptive Dual-Branch Token Sparsification via Spatial Information Density
Singularity-aware Optimization via Randomized Geometric Probing: Towards Stable Non-smooth Optimization
AnyCanvas: Potential Field Guidance for Training-Free Spatial Control in Text-to-Image Diffusion
Revisiting the Role of Pretrained Weights in Model Merging: On Near-Optimality within the Core Subspace
SpatioLM: Towards General Physical Spatial Intelligence in Vision-Language Models
WorldMirror: Universal 3D World Reconstruction with Any-Prior Prompting
Revealing Differences in Multi-Modal Embeddings via Constrained Kernel Analysis
Decentralized Bandits without Global Clock for Dynamic Matching Market
Causal Dependency-Aware Unsupervised Routing for Large Reasoning Models
SPARKLING: Balancing Signal Preservation and Symmetry Breaking for Width-Progressive Learning
LC-QAT: Data-Efficient 2-Bit QAT for LLMs via Linear-Constrained Vector Quantization
Unveiling the Visual Counting Bottleneck in Vision-Language Models
Multimodal Meta-Verifier with Explicit Structured Recalibration
Efficient Distributed MLLM Training with ModalGlue
The Illusion of Generalization: Instruction-Following, Task Bias and Contamination in Tabular Language Model Evaluation
Harnessing Reasoning Trajectories for Hallucination Detection via Answer-agreement Representation Shaping
Unified Multimodal Autoregressive Modeling with Shared Context—Visual Tokenizer is Key to Unification
TimeSAE: Sparse Decoding for Faithful Explanations of Black-Box Time Series Models
VideoSeeker: Native Interleaved Clue Seeking for Long Video Multi-Hop Reasoning
LynX: Token Interface Alignment for Video+X LLMs
Focusing Where Vision Matters: Selective Training for Large Vision Language Models via Visual Information Gain
Vector Quantization using Gaussian Variational Autoencoder
Explaining Data Mixing Scaling Laws
Calibrating Generative Models to Distributional Constraints
Primal-Spectral Generative Modeling: Fast Analytical Generation via Pseudoinverse Lévy Inversion
HIVE-3D: Hierarchical Voxel Enhancement for High-Quality 3D Scene Generation
SJD-SV: Speculative Jacobi Decoding with Semantics Verification for Autoregressive Image Generation
3D MeanFlow: One-Step Point Cloud Completion and Generation via Average-Velocity Transport
Exploring Data-Free LoRA Transferability for Video Diffusion Models
Autoregression with Self-Token Prediction
Interpreting and Steering State-Space Models via Activation Subspace Bottlenecks
Mitigating Noise-Induced Layout Priors for Object Counting in Diffusion Models
Rethinking Pretraining Data Detection for LLMs: From Local to Global
Variational Bayesian Flow Network for Graph Generation
PolyFlow: Safe and Efficient Polytope-Constrained Flow Matching with Constraint Embedding and Projection-free Update
Efficient Diffusion Models via Time Step Optimization with Consistent Training and Inference Constraints
FunPhase: A Periodic Functional Autoencoder for Motion Generation via Phase Manifolds
TarGATE: Target-Aware Data Selection via Token-Attenuation Gates
Responsible Text-to-Image Diffusion: Interpretable and Linearly Controllable Semantics for Fair and Safe Generation
Proximal-Based Generative Modeling for Bayesian Inverse Problems
Learning $U$-Statistics with Active Inference
AlignVid: Taming Visual Dominance via Training-Free Attention Modulation in Text-guided Image-to-Video Generation
Pose-ICL: 3D-Aware In-Context Learning for Pose-Controllable Subject Customization
Multiple Choice Learning of Low-Rank Adapters for Language Modeling
Universal Multiclass Transductive Online Learning
Vision in One Vector: Implicit Visual Compression with Diffusion Foundation Models
RevealLayer: Disentangling Hidden and Visible Layers via Occlusion-Aware Image Decomposition
Nonparametric Data Attribution for Diffusion Models
Beyond Pixel Context Windows: Neural World Simulators with Persistent 3D State
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
Improving Graph Transformers via Global Structural Priors
LoRe: Adaptive Interaction-Evaluation Routing with Per-step Interaction Budgets for Iterative Graph Solvers
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
Learning Long Range Spatio-Temporal Representations over Continuous Time Dynamic Graphs with State Space Models
Learning the Neighborhood: Contrast-Free Multimodal Self-Supervised Molecular Graph Pretraining
Dual-channel Dynamic Graph Neural Networks with Adaptive Adjacency Learning and Multi-scale Representation Fusion
Graph Alignment for Benchmarking Graph Neural Networks and Learning Positional Encodings
On the Expressive Power of GNNs to Solve Linear SDPs
Rel-MOSS: Towards Imbalanced Relational Deep Learning on Relational Databases
Fixed Aggregation Features Can Rival GNNs
Structure-Centric Graph Foundation Model via Geometric Bases
Full-Spectrum Graph Neural Network: Expressive and Scalable
Graph Neural Networks Are Not Continuous Across Graph Resolutions
A Unifying Relational Perspective on Expressive Lottery Tickets
Adaptive Memory Retention in Dynamic Graphs
Exploration-free Algorithms for Multi-group Mean Estimation
Certificates for Complex-Compatible Learned Cochain Laplacians
FiRE: Fine-grained Ranking Evaluation for Machine Translation
Process Reward Models That Think
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
Thinking with Geometry: Active Geometry Integration for Spatial Reasoning
UrbanMLLM: Joint Learning of Cross-view Imagery for Urban Understanding
LongCoT: Benchmarking Long-Horizon Chain-of-Thought Reasoning
From Extraction to Deduction: Resolving Functional Misalignment in RAG via a Collaborative Critic-Reasoner Framework
Midtraining Bridges Pretraining and Posttraining Distributions
Credibility-Aware Weighting Federated Causal Discovery for Time Series
SciPredict: Can LLMs Predict the Outcomes of Scientific Experiments in Natural Sciences?
LiveNewsBench: Evaluating LLM Web Search Capabilities with Freshly Curated News
Navigating the Pareto Frontier of Alignment:Spectrum-Adaptive Fine-Tuning for LLMs
Context-level Language Modeling by Learning Predictive Context Embeddings
Shared Semantics, Divergent Mechanisms: Unsupervised Feature Discovery by Aligning Semantics and Mechanisms
When Search Goes Wrong: Red-Teaming Web-Augmented Large Language Models
TimeMRA: LLM-Empowered Time Series Forecasting via Multi-Scale Retrieval-Augmented Representations
MixReasoning: Switching Modes to Think
Geometry of Reason: Spectral Signatures of Valid Mathematical Reasoning
ParaTool: Shifting Tool Representations from Context to Parameters
Unifying Heterogeneous Multi-Modal Remote Sensing Detection Via Language-Pivoted Pretraining
PISA: Privacy-Preserving Split Adaptation with Model IP Protection
KORE: Enhancing Knowledge Injection for Large Multimodal Models via Knowledge-Oriented Controls
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
Any-Diffusion: Unified Multimodal Understanding and Generation with Masked Discrete Diffusion
PRISM: Gauge-Invariant Tangent-Space Differentially Private LoRA
Beyond Mode Collapse: Distribution Matching for Diverse Reasoning
Preserve-Then-Quantize: Balancing Rank Budgets for Quantization Error Reconstruction in LLMs
RGMem: Renormalization Group–inspired Memory Evolution for Language Agents
Closing the Loop: Universal Repository Representation with RPG-Encoder
Does Math Reasoning Improve General LLM Capabilities? Understanding Transferability of LLM Reasoning
The First Drop of Ink: Nonlinear Impact of Misleading Information in Long-Context Reasoning
DevEvol: Benchmarking LLM Agents on Continuous Software Evolution
Reasoning-preserved Efficient Distillation of Large Language Models via Activation-aware Initialization
Breaking the Exploration Bottleneck: Rubric-Scaffolded Reinforcement Learning for General LLM Reasoning
Characterizing, Evaluating, and Optimizing Complex Reasoning
How2Everything: Mining the Web for How-to Procedures to Evaluate and Improve LLMs
Symbolic Mixture-of-Experts: Adaptive Skill-based Routing for Heterogeneous Reasoning
LazyAttention: Efficient Retrieval-Augmented Generation with Deferred Positional Encoding
Facts in Stats: Impacts of Pretraining Diversity on Language Model Generalization
From Patches to Plans: Reasoning Distillation for Repository-Level Program Repair
Compile to Compress: Boosting Formal Theorem Provers by Compiler Outputs
SAME: Stabilized Mixture-of-Experts for Multimodal Continual Instruction Tuning
Retriever Portfolios: A Principled Approach to Adaptive RAG
More Edits, More Stable: Understanding the Lifelong Normalization in Sequential Model Editing
On Training Large Language Models for Long-Horizon Tasks: An Empirical Study of Horizon Length
Calibrated Knowledge Aggregation in Bayesian Mixture-of-Experts for Continual VQA
A Minimal Agent for Automated Theorem Proving
SmartThinker: Progressive Chain-of-Thought Length Calibration for Efficient Large Language Model Reasoning
TileQ: Efficient Low-Rank Quantization of Mixture-of-Experts with 2D Tiling
How Transformers Represent Hierarchies: A Local-to-Global Mechanism
Towards Atoms of Large Language Models
AlienLM: Alienization of Language for API-Boundary Privacy in Black-Box LLMs
Antidistillation Fingerprinting
World-Model Inspired Emotion-aware Token Refinement for Training-Free Multimodal Emotion Recognition
LK Losses: Direct Acceptance Rate Optimization for Speculative Decoding
WUSH: Near-Optimal Adaptive Transforms for LLM Quantization
Shape of Thought: Progressive Object Assembly via Visual Chain-of-Thought
BIOARC: Discovering Optimal Neural Architectures for Biological Foundation Models
Configurable Reward Model for Balanced Safety Alignment
A3: an Analytical Low-Rank Approximation Framework for Attention
BeaconKV: Key-Value Cache Compression Guided by Beacon Queries for Efficient Large Reasoning Model Inference
DenseSteer: Steering Small Language Models towards Dense Math Reasoning
CoRe: Context-Robust Remasking for Diffusion Language Models
Learning from Fine-Grained Visual Discrepancies: Mitigating Multimodal Hallucinations via In-Context Visual Contrastive Optimization
ParamMem: Augmenting Language Agents with Parametric Reflective Memory
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
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
HiCI: Hierarchical Construction–Integration for Long-Context Attention
Position: Artificial Intelligence Needs Meta Intelligence - the Case for Metacognitive AI
Towards Execution-Grounded Automated AI Research
Look on Demand: A Cognitive Scheduling Framework for Visual Evidence Acquisition in Multimodal Reasoning
Distributed Stochastic $K$-Level Optimization Over Networks
AIR: Post-training Data Selection for Reasoning via Attention Head Influence
Approximation Preserving Coresets
NanoSpec: Accelerating Speculative Decoding using Minimalist In-Context Vocabularies
Provably Learning Attention with Queries
FIRE: Learning to Navigate and Act on Real-World Files via Stateful Reinforcement Learning
Decouple Searching from Training: Scaling Data Mixing via Model Merging for Large Language Model Pre-training
Darwinian Memory: A Training-Free Self-Regulating Memory System for GUI Agent Evolution
Probability-Entropy Calibration: An Elastic Indicator for Adaptive Fine-tuning
Disentangling meaning from language in LLM-based machine translation
Attention Illuminates LLM Reasoning: The Uncovered Preplan-and-Anchor Rhythm Enables Fine-Grained Policy Optimization
A²RBench: An Automatic Paradigm for Formally Verifiable Abstract Reasoning Benchmark Generation
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
The Geometric Reasoner: Manifold-Informed Latent Foresight Search for Long-Context Reasoning
Correcting in Hindsight: Editing Past Key-Value States for Robust LLM Reasoning
Recursive Models for Long-Horizon Reasoning
Know Thyself, Know Thy User: Intrinsic Dual-Perspective Reasoning for Role-Playing LLMs
DARTS: Distribution-Aware Active Rollout Trajectory Shaping for Accelerating LLM Reinforcement Learning
Compute as Teacher: Turning Inference Compute Into Reference-Free Supervision
LORD-GoF: A Robust Online Detection Approach for LLM Watermarks in Sparse and Mixed Streams
Algorithmic Primitives and Compositional Geometry of Reasoning in Language Models
Diving into Kronecker Adapters: Component Design Matters
Towards Reliable Marking and Verification of AI-Generated Text via Geometry-aware Sentence-level Watermarking
Solving Physics Olympiad via Reinforcement Learning on Physics Simulators
Learning to Remember, Learn, and Forget in Attention-Based Models
AtomWorld: A Benchmark for Evaluating Spatial Reasoning in Large Language Models on Material Structures
LUGS: Latent-aware Guidance for Efficient Unmasking in Diffusion Large Language Models
Adversarial Reinforcement Learning for Robust Diffusion Large Language Model Unlearning
ViewMask-1-to-3: Multi-View Consistent Image Generation via Multimodal Diffusion Models
Sparks of Cooperative Reasoning: LLMs as Strategic Hanabi Agents
Multilingual Safety Alignment via Representation-Space Separability
Predicting the Order of Upcoming Tokens Improves Language Modeling
RaBiT: Residual Aware Binarization Training for Accurate and Efficient LLMs
Adaptive Time Series Reasoning via Segment Selection
Stop When Further Reasoning Won’t Help: Attention-State Adaptive Generation in Reasoning Models
Grouter: Decoupling Routing from Representation for Accelerated MoE Training
Attention Sinks in Diffusion Transformers: A Causal Analysis
Interpretability Transfer from Language to Vision via Sparse Autoencoders
$A_2$DEPT: Large Language Model–Driven Automated Algorithm Design via Evolutionary Program Trees
Bias in Zeroth-Order Normal Estimation for Decision-Based Attacks
Private and Stable Test-time Adaptation with Differential Privacy
ProMeCD: Unifying Long-Tailed and Noisy Label Learning via White-Box Control
You Don't Protect if You Don't Expect: Breaking the Key Assumption behind CLIP's Test-Time Defenses
Riemannian Networks over Full-Rank Correlation Matrices
A Coin Flip for Safety: LLM Judges Fail to Reliably Measure Adversarial Robustness
Toward Understanding Adversarial Distillation: Why Robust Teachers Fail
``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
Non-Parametric Probabilistic Robustness: A Conservative Risk Estimator under Unknown Perturbation Distributions
Certified Robustness under Heterogeneous Perturbations via Hybrid Randomized Smoothing
Higher-Order Certified Robustness for Regression
LLM Watermark Evasion via Bias Inversion
Hidden in Plain Sight -- Class Competition Focuses Attribution Maps
Causal-JEPA: Learning World Models through Object-Level Latent Interventions
Clustering in Deep Stochastic Transformers
GenDA: Generative Data Assimilation on Complex Urban Areas via Classifier-Free Diffusion Guidance
Hyperbolic Neural Operator
Global Plane Waves From Local Gaussians: Periodic Charge Densities in a Blink
Physics-Informed Self-Supervised Learning on Efficient Electron-Density Images for Organic Material Property Prediction
Graph Rewiring based on Flow Alignment for Improving Fluid Simulation
HSGG: Training-Free Hierarchical Scene Graph Generation with Geometry-Guided Relation Reasoning
Adaptive Physics Transformer with Fused Global-Local Attention for Subsurface Energy Systems
Mesh Based Simulations with Spatial and Temporal awareness
Efficient Training of Boltzmann Generators Using Off-Policy Log-Dispersion Regularization
E2Former-V2: On-the-Fly Equivariant Attention with Linear Activation Memory
Multimodal Crystal Flow: Any-to-Any Modality Generation for Unified Crystal Modeling
G-RANS: Generalizable Residual-Aware Neural Solvers for Sparse Systems
Self-Supervised Learning as Discrete Communication
Order Matters in Retrosynthesis: Structure-aware Generation via Reaction-Center-Guided Discrete Flow Matching
Data-driven Mixed Integer Optimization through Probabilistic Multi-variable Branching
The Heterogeneous Safety Impacts of Benign Multilingual Fine-Tuning
Position: AI for Science Should Treat Measurement-to-Dataset Pipelines as Inference Components
Intrinsic Gradient Suppression for Label-Noise Prompt Tuning in Vision–Language Models
DocOS: A Benchmark for Proactive Document-Guided Actions in GUI Agents
Self-Evolving LLM Agents under Offline Data Support
Memory as Dynamics: Learning Reliability-Guided Predictive Models for Online Video Perception
Interactive Person Retrieval via Multi-Turn Multimodal Conversation
Code2Video: A Code-centric Paradigm for Educational Video Creation
Dynamic Multimodal Evaluation via Knowledge-Enhanced Benchmark Evolution
Emergent Analogical Reasoning in Transformers
Spike Camera Autofocus via Frequency-Domain Spectral-Centroid Migration
PVDepth: Panoramic Video Depth Estimation via Geometry-Aware Spatiotemporal Adaptation
Learning 3D-Gaussian Simulators from RGB Videos
Code2Worlds: Empowering Coding LLMs for 4D World Generation
Decoupling Skeleton and Flesh: Efficient Multimodal Table Reasoning with Disentangled Alignment and Structure-aware Guidance
Just Noticeable Difference Modeling for Deep Visual Features
Walrus: A Cross-domain Foundation Model for Continuum Dynamics
NanoQuant: Efficient Sub-1-bit Quantization of Large Language Models
Dual-Latent Memory Routing for Vision-Language Reasoning
Zero-Shot Text-to-Motion Evaluation using Video Language Models
Prototype Transformer: Towards Language Model Architectures Interpretable by Design
Causal-EPIG: Causally Aligned Active CATE Estimation
Image Restoration via Diffusion Models with Dynamic Resolution
Exploiting Hankel-Toeplitz Structures for Fast Computation of Kernel Precision Matrices
LaRI: Layered Ray Intersections for Single-view 3D Geometric Reasoning
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
Hyperbolic Hierarchical Alignment for Video-Based Visible-Infrared Person Re-Identification
VlogReward: Learning Multi-Dimensional Evaluation for Vlog Editing
Video-BCI: Bayesian Cognitive Integration of Self-Prior Hypotheses for Video Understanding
MM-Snowball: Evaluating and Mitigating Hallucination Snowballing in Multimodal Multi-turn Dialogue
Q-CLIP: Unleashing the Power of Vision-Language Models for Video Quality Assessment through Unified Cross-Modal Adaptation
A robust PPG foundation model using multimodal physiological supervision
Continual GUI Agents
Fair-FedMOE: Group-Fair One-Shot Federated Learning via Prototype-Guided Experts for Medical Imaging Analysis
Enabling Faithful Camera Control in Video Diffusion through Geometry-Flow-Guided Noise Warping
Rethinking Genomic Modeling Through Optical Character Recognition
PhoStream: Benchmarking Real-World Streaming for Omnimodal Assistants in Mobile Scenarios
CoMem: Context Management with A Decoupled Long-Context Model
Position: Modular Safety Guardrails Are Necessary for Foundation-Model-Enabled Robots in the Real World
A Direct Approach for Handling Contextual Bandits with Latent State Dynamics
Position: Benchmarks for Vision–Language Models in Urban Perception Should Be Reliability-Aware and Negotiated
Benchmarking Physics-Informed Time-Series Models for Operational Global Station Weather Forecasting
OPTION: Optimal Transport–Guided Flow Matching for Incomplete and Unaligned Multi-View Clustering
InfraRL: A Benchmark for Constrained Resource Allocation in Large-Scale Infrastructure Asset Management
SMAC: Score-Matched Actor-Critics for Robust Offline-to-Online Transfer
SPAR: Support-Preserving Action Rectification
Bottleneck-Guided Spectral Subgoals For Offline Goal-Conditioned RL
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
Frictional Q-Learning
Discriminative Visual Process Rewards for Scaling Thinking at Test-Time with Images
Off-Policy Learning in Large Action Spaces: Optimization Matters More Than Estimation
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: AI Evaluations Should be Grounded on a Theory of Capability
Stabilizing the Q-Gradient Field for Policy Smoothness in Actor-Critic Methods
Mind the budget: Accelerating Deep Reinforcement Learning using Early Exit Neural Networks
Safe In-Context Reinforcement Learning
Cardinality-Invariant Neural Operator Policies for Scalable PDE Control
EAPO: Enhancing Policy Optimization with On-Demand Expert Assistance
From Interaction Trajectories to Prompt Rules: Credit Assignment for Multi-Agent Prompt Optimization
Posterior Behavioral Cloning: Pretraining BC Policies for Efficient RL Finetuning
Intentional Updates for Streaming Reinforcement Learning
PETS: A Principled Framework Towards Optimal Trajectory Allocation for Efficient Test-Time Self-Consistency
Bridging Scaling Laws to On-Policy Reinforcement Learning via Adaptive Batch Scaling
Softmax as Linear Attention in the Large-Prompt Regime: a Measure-based Perspective
Online Robust Reinforcement Learning with General Function Approximation
Learning Generalizable Skill Policy with Data-Efficient Unsupervised RL
Fast Non-Episodic Finite-Horizon RL with K-Step Lookahead Thresholding
IPMark: A Sentence-Level Watermark for LLMs with Hierarchical Personalization and Efficient Detection
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
Optimization with Access to Auxiliary Information
Position: Human-Centric Vision Requires Topological Generalization Beyond Fixed Skeletal Topologies
Position: AI Evaluation Should Work With Humans
Infinite-World: Scaling Interactive World Models to 1000-Frame Horizons via Pose-Free Hierarchical Memory
DSGym: A Standardized and Holistic Framework for Advancing Data Science Agents
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
Find, Fix, Reason: Context Repair for Video Reasoning
A Time-Reparameterized Cumulative Intensity Extrapolation Sampler for Discrete Flow Matching
SkelHCC: A Hyperbolic CLIP-Driven Cache Adaptation Framework for Skeleton-based One-Shot Action Recognition
FlatLand: Personalized Graph Federated Learning via Tailored Lorentz Space
PnP-Corrector: A Universal Correction Framework for Coupled Spatiotemporal Forecasting
PRM-PBE: Process Reward Model for Reinforcement Learning in Programming-by-Example
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
Subspace-Aware Feature Reshaping for Open-Set Graph Class-Incremental Learning
From Teacher Pathways to Invariant Manifolds: Consensus Subspace Distillation for TSFMs
LOZO+: Provably Efficient Zeroth-Order Fine-Tuning via Greedy Low-Rank Subspace Selection
WeDLM: Reconciling Diffusion Language Models with Standard Causal Attention for Fast Inference
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
AICrypto: Evaluating Cryptography Capabilities of Large Language Models
SDiD：Shared diffusion prior for efficient distributed stereo image compression
Annotations Mitigate Post-Training Mode Collapse
Rethinking Personalization in Large Language Models at the Token Level
Geometry-Preserving Orthonormal Initialization for Low-Rank Adaptation in Reinforcement Learning
BrokenMath: A Benchmark for Sycophancy in Theorem Proving with LLMs
InfoLaw: Information Scaling Laws for Large Language Models with Quality-Weighted Mixture Data and Repetition
PromptRL: Prompt Matters in RL for Flow-Based Image Generation
AffIn-Space: Learning Affine-Invariant Representations for 3D Spatial Understanding with MLLMs
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
A Constrained Optimization Perspective of Unrolled Transformers
Cross-task Calibration for Asynchronous Federated Continual Learning
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
Polaris: Coupled Orbital Polar Embeddings for Hierarchical Concept Learning
Recontextualization Mitigates Specification Gaming Without Modifying the Specification
Universal Skeleton Understanding via Differentiable Rendering and MLLMs
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
D-CORE: Incentivizing Task Decomposition in Large Reasoning Models for Complex Tool Use
Unsupervised Process-Aware Coreset Selection for In-Context Learning
MME-Reasoning: A Broad-Spectrum Benchmark for Evaluating Logical Reasoning in MLLMs
Optimizing KV Cache Eviction from an Output Perturbation Perspective
Grokking Finite-Dimensional Algebra
Towards Understanding Steering Strength
Patterning: The Dual of Interpretability
Context-free Recognition with Transformers
Unifying Low Dimensional Spectra in Deep Learning
Optimal Stopping in Latent Diffusion Models
Information dynamics and Memory in Neural Networks through Fisher Information Diffusion
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
Sequential Group Composition: A Window into the Mechanics of Deep Learning
From Welfare to Utility: Generalized Objectives in Budget-Feasible Procurement
What Preferences Can—and Cannot—Predict in Multi-Agent Online Learning
Nash Equilibria in Games with Playerwise Concave Coupling Constraints: Existence and Computation
Theory of Continual Learning Against Data Poisoning Attacks
Multi-Level Strategic Classification: Incentivizing Improvement through Promotion and Relegation Dynamics
Enhancing Affine Maximizer Auctions with Correlation-Aware Payment
Delegation and Verification under AI
Deep Reinforcement Learning Finds Bayes-Nash Equilibrium in Competitive Newsvendor Problems
Knowing Who, Not How Much: Learning-Augmented Mechanisms for Consumer Utility Maximization
Optimal Regularization for Performative Learning
SlideSparse: Fast and Flexible (2N-2):2N Structured Sparsity
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
SciNet: Evaluating AI Agents in Relation-Aware Scientific Literature Retrieval
Beyond Explicit Edges: Robust Reasoning over Noisy and Sparse Knowledge Graphs
Unifying and Optimizing Data Values for Selection via Sequential Decision-Making
DMCO: Budget-Aware Co-Optimization of Data Cleaning and AutoML
Counterfactual Residual Data Augmentation for Regression
Beyond Benchmarks: Toward Causally Faithful Evaluation of Large Language Models
AppWorld-UL: Benchmarking Diverse Agent-User Interactions for Tool-Use
Routing and Reasoned Evaluation with Large Language Models
Probing the Knowledge Boundary: An Interactive Agentic Framework for Deep Knowledge Extraction
CodeTaste: Can LLMs Generate Human-Level Code Refactorings?
Untied Ulysses: Memory-Efficient Context Parallelism via Headwise Chunking
Scalable Training of 3D Gaussian Splatting via Out-of-Core Optimization
SoftJAX & SoftTorch: Empowering Automatic Differentiation Libraries with Informative Gradients
DITRON: Distributed Multi-level Tiling Compiler for Parallel Tensor Programs
Convolutional Learnable-Group Weightless Neural Network
Asymmetric conformal prediction with penalized kernel sum-of-squares
Rethinking Time-Series Imputation as Conditional Inference along Temporal Evolution
Relevance-Based Embeddings: Lightweight Candidate Selection via Heavy Ranker Calls
Independent Component Discovery in Temporal Count Data
From Content to Knowledge: Lightning Fast Long-Video Understanding with Neural Knowledge Representations
Representation Unlearning: Forgetting through Information Compression
Scalable and Interpretable Representation Alignment with Ordinal Similarity
Normalizing Diffusion Kernels with Optimal Transport
Towards Rule-Based Knowledge Sharing in Federated Learning
An Asymmetric Latent Factorization-of-Tensors Model for Relation Extraction
Wait, Wait, Wait... Why Do Reasoning Models Loop?
Contrastive Order Learning: A General Framework for Ordinal Regression
FlashSinkhorn: IO-Aware Entropic Optimal Transport on GPU
Cross-View Lewis Weight Fusion Empowering Exemplar Replay for Federated Class-Incremental Learning
Step-Size Stability in Stochastic Optimization: A Theoretical Perspective
Hard Labels In! Rethinking the Role of Hard Labels in Mitigating Local Semantic Drift
Learning Generalized Label Distributions
Divisiveness-Consistent Label Distribution Learning
Retrospective Feature Estimation for Continual Learning
Distilling Linearized Behavior into Non-linear Fine-Tuning for Effective Task Arithmetic
Don't Reinvent the Wheel, Just Realign the Spokes: Resource-Efficient Federated Fine-Tuning via Rank-Wise Expert Assembly
TuneAhead: Predicting Fine-tuning Performance Before Training Begins
Gradient Transformer: Learning to Generate Updates for LLMs
SaTeen: Learning Structural Alignment for Continual Test-Time Adaptation
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
Turning Back Without Forgetting: Selective Backward Refinement for Parameter-Efficient Continual Learning
SOTAlign: Semi-Supervised Alignment of Unimodal Vision and Language Models via Optimal Transport
Particle Flow for Learning from Label Proportions
Rethinking Memory in Continual Learning: Beyond a Monolithic Store of the Past
NeuralFLoC: Neural Flow-Based Joint Registration and Clustering of Functional Data
Efficient Tail-Aware Generative Optimization via Flow Model Fine-Tuning
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
Beyond Majority Voting: LLM Aggregation by Leveraging Higher-Order Information
Explicitly Modeling Censoring Produces Superior Survival Predictors
Courtroom Analogy: New Perspective on Uncertainty-Aware Classification
Position: Robust AI Personalization Will Require a Human Context Protocol
Natural Hypergradient Descent: Algorithm Design, Convergence Analysis, and Parallel Implementation
Unifying Adversarial Robustness and Training Across Text Scoring Models
IACW: Intent-Aware Controllable Watermarking for Scalable Authorial Intent Attribution
ConEx: Human-Interpretable Saliency Maps via Concept-Aware Attribution
Towards Long-Horizon Interpretability: Efficient and Faithful Multi-Token Attribution for Reasoning LLMs
Exactly Computing do-Shapley Values
Do Language Models Track Entities Across State Changes?
The Catastrophic Failure of *the* k-Means Algorithm in High Dimensions, and How Hartigan's Algorithm Avoids It
Spurious Rewards Paradox: Mechanistically Understanding How RLVR Activates Memorization Shortcuts in LLMs
Functional Decomposition and Shapley Interactions for Interpreting Survival Models
Neural Concept Verifier: Scaling Prover-Verifier Games via Concept Encodings
Learning to Watermark in the Latent Space of Generative Models
TT-Sparse: Learning Sparse Rule Models with Differentiable Truth Tables
Uncovering Competency Gaps in Large Language Models and Their Benchmarks
Diagnosing Multi-step Reasoning Failures in Black-box LLMs via Stepwise Confidence Attribution
Position: Measuring Human Preferences in RLHF is a Social Science Problem
PMSPO: Progressive Matching and Semantic-Aware Policy Optimization for Camouflaged Object Detection
Position: Evaluating LLMs in Finance Requires Explicit Bias Consideration
Position: Large Language Models Should Learn Personalized Rather Than Aggregated Human Preferences
One Bias After Another: Mechanistic Reward Shaping and Persistent Biases in Language Reward Models
The Personality Illusion: Revealing Dissociation Between Self-Reports & Behavior in LLMs
Alignment Pretraining: AI Discourse Causes Self-Fulfilling (Mis)alignment
Emergent Alignment via Competition
MORALISE: A Structured Benchmark for Moral Alignment in Visual Language Models
On the Limits of LLM Adaptability: Impact of LLM Pre-Training on Annotation Task Performance
More Capable, Less Cooperative? When LLMs Fail at Zero-Cost Collaboration
Wikipedia in the Era of LLMs: Evolution and Risks
Position: Agentic Safety is an Epistemic Property, Not a Behavioral One
Position: AI/ML Deepfake Research is Misaligned with AI Generated Non-Consensual Intimate Imagery (AIG-NCII)
A Unified Framework for Diffusion Model Unlearning with f-Divergence
The Oversight Game: Learning to Cooperatively Balance an AI Agent's Safety and Autonomy
TraceRouter: Robust Safety for Large Foundation Models via Path-Level Intervention
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
Safe Autoregressive Image Generation with Iterative Self-Improving Codebooks
A Theoretical Game of Attacks via Compositional Skills
Emergence of Hierarchical Emotion Organization in Large Language Models
DualOptim+: Bridging Shared and Decoupled Optimizer States for Better Machine Unlearning in Large Language Models
ABC-Bench: An Agentic Bio-Capabilities Benchmark for Biosecurity
Collaborative Threshold Watermarking
Turning Bias into Bugs: Bandit-Guided Style Manipulation Attacks on LLM Judges
Semantic Router: On the Feasibility of Hijacking MLLMs via a Single Adversarial Perturbation
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
Echoes within the Reasoning: Stealth and Effective Watermarking via Chain of Thought
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
HyperPotter: Spell the Charm of High-Order Interactions in Audio Deepfake Detection
Next-Gen CAPTCHAs: Leveraging the Cognitive Gap for Scalable and Diverse GUI-Agent Defense
Co-RedTeam: Orchestrated Security Discovery and Exploitation with LLM Agents
Ripple Perturbations Through Structure: Likelihood-Constrained Adversarial Attacks on Heterogeneous Tabular Data
Position: Generative Models Erode Temporal Learning Through Market Selection
Position: Neglecting the Sustainability of AI is Fuelling a Global AI Arms Race
Expressive Graph Neural Networks via Equivariant Use of Noise
Position: Prompts for Public-Sector LLMs Should Be Governed as Commons
Evolving Interpretable Constitutions for Multi-Agent Coordination
LO-BCQ: Locally Optimal Block Clustered Quantization for 4-bit (W4A4) LLM Inference
RTInfer: Exploiting Concurrency for Multiple Real-Time DNN Inference 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
CauchyNet: Compact and Data-Efficient Learning using Holomorphic Activation Functions
Equilibrium Reasoners: Learning Attractors Enables Scalable Reasoning
Cross-Modal Knowledge Distillation without Paired Data: Theoretical Foundations and Algorithms
The Ideal Expression Is Not a Local Optimum: A Revisit of EQL with Zero-Point Constraints
Learning When to Attend: Conditional Memory Access for Long-Context LLMs
InfoFlow KV: Information-Flow-Aware KV Recomputation for Long Context
Position: Modular Memory is the Key to Continual Learning Agents
Position: Multiple Definitions & Unrealistic Assumptions of Model Collapse Distract from Real World Threats
Align Forward, Adapt Backward: Closing the Discretization Gap in Logic Gate Networks
Position: Quantum Program Generation Must Prioritize Validity Over Probabilistic Scaling
Feature-aware (Hyper)graph Generation via Next-Scale Prediction
Stable Velocity: A Variance Perspective on Flow Matching
SE(n)-Invariant Flow Matching: A General Framework with Application to Object Reassembly
Is Fixing Schema Graphs Necessary? Full-Resolution Graph Structure Learning for Relational Deep Learning
(1D) Ordered Tokens Enable Efficient Test-Time Search
Quantum latent distributions in deep generative models
Constrained Flow Optimization via Sequential Fine-Tuning for Molecular Design
STAR-VAE: Structured Topology-Aware Regularization for Audio Reconstruction and Generation
Variational Flow Maps: Make Some Noise for One-Step Conditional Generation
Contrastive Flow Map Matching
DetailMaster: Can Your Text-to-Image Model Handle Long Prompts?
Overclocking Electrostatic Generative Models
How to guide your flow: Steering flow maps for rapid test-time alignment
Sparse Autoencoders are Topic Models
Q-Tab: Quantized Tabular Data Generator
Which Algorithms Can Graph Neural Networks Learn?
Is Graph Mixup Beneficial? Investigating Interpolation And Empirical Performance of Graph Mixup Methods
On Efficient Scaling of GNNs via IO-Aware Layers Implementations
Identifiable Equivariant Networks are Layerwise Equivariant
Investigating Continual Pretraining in Large Language Models: Insights and Implications
Position: Prompting Intent Should Be Audited in LLM-Assisted Peer Review
Understanding LoRA as Knowledge Memory: An Empirical Analysis
POLCA: Stochastic Generative Optimization with LLM
Hierarchical Abstract Tree for Cross-Document Retrieval Augmented Generation
Gradient-Aware Scheduling: Coupling Curriculum and Staleness for Async Reinforcement Learning
Attention Sinks as Internal Signals for Hallucination Detection in Large Language Models
How Powerful are LLMs in Generating Program Specifications?
Omni-Perception Policy Optimization for Multimodal Emotion Reasoning
Escaping Whack-a-Mole: Code Documentation Optimization via Dependency-Guided Bi-level Search
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)
LLMInertia: Adaptive Counter-Inertial Reasoning to Improve Evidence Faithfulness in Large Language Models
Schema-Guided World Modeling for Understanding Hierarchical Visual Dynamics
Gecko: A Simulation Environment with Stateful Feedback for Refining Agent Tool Calls
Context-Aware Reaonser : Enhancing Contextual Reasoning in Multimodal Large Language Models
ConvexBench: Can LLMs Recognize Convex Functions?
PlugMem: A Task-Agnostic Plugin Memory Module for LLM Agents
$\tau^2$-Bench: Evaluating Conversational Agents in a Dual-Control Environment
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
Rethinking Thinking Tokens: LLMs as Improvement Operators
AnyEdit++: Adaptive Long-Form Knowledge Editing via Bayesian Surprise
Training-Free Hierarchical Working Memory for Small Language Model Agents
CSPLoRA: Confidence-Guided Structure Planning for Low-Rank Adaptation
One-Way Policy Optimization for Self-Evolving LLMs
From Prompts to Responses: Dual-Sided Data Leakage and Defense in Split Large Language Models
Rethinking LLM Ensembling from the Perspective of Mixture Models
Coupled Variational Reinforcement Learning for Language Model General Reasoning
How Does Reasoning Flow? Tracing Attention-Induced Information Flow for Targeted RL in LLMs
MEMO: Memory-Augmented Model Context Optimization for Robust Multi-Turn Multi-Agent LLM Games
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
MRPO: Magnitude-Regularized Policy Optimization via L1 Constraints
Truthfulness Does Not Scale Like Reasoning: Why Polling Fails as a Proxy Verifier
MoDA: Modulation Adapter for Fine-Grained Visual Understanding in Instructional MLLMs
Structure Enables Effective Self-Localization of Errors in LLMs
Can LLMs Reason Structurally? Benchmarking via the lens of Data Structures
FAFO: Lossy KV Cache Compression for Lossless Inference Acceleration via Draftless Fumble Decoding
Imagination Helps Visual Reasoning, But Not Yet in Latent Space
The Bridge-Garden Dilemma in LLM Distillation: Why Mixing Hard and Soft Labels Works
When LLMs Develop Languages: Symbolic Communication for Efficient Multi-Agent Reasoning
DRIFT: Decoupled Rollouts and Importance-Weighted Fine-Tuning for Efficient Multi-Turn Optimization
Sycophancy Towards Researchers Drives Performative Misalignment
Conformal Path Reasoning: Trustworthy Knowledge Graph Question Answering via Path-Level Calibration
Towards Understanding Massive Activations in Attention Sink Mechanism
COBRA: Contribution-Based Bayesian Rank Allocation for Parameter-Efficient Fine-Tuning
TAMPO: Task- and Model-Aware Automatic Prompt Optimization for Robust and Controllable Auto-Routing in LLM-based Systems
What Makes Effective Supervision in Latent Chain-of-Thought: An Information-Theoretic Analysis
MetaphorVU: Towards Metaphorical Video Understanding
Task-and-Model-Aware Fractal-Consistency for Efficient LLM Reasoning
PonderLM-2: Pretraining LLM with Latent Thoughts in Continuous Space
Token-Level LLM Collaboration via FusionRoute
Convergent World Representations and Divergent Tasks
Multi-Way Representation Alignment
Self-Soupervision: Cooking Model Soups without Labels
Balancing Learning Rates Across Layers: Exact Two-Step Dynamics and Optimal Scaling in Linear Neural Networks
How Out-of-Distribution Detection Learning Theory Enhances Transformer: Learnability and Reliability
Steering Out-of-Distribution Generalization with Concept Ablation Fine-Tuning
Geometric and Stochastic Analysis of Discontinuities in Sparse Mixture-of-Experts
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
Fractional is Better: Learnable Derivative Orders in Neural Operator Learning
Deriving Neural Scaling Laws from the Statistics of Natural Language
Generalization and Scaling Laws for Mixture-of-ExpertsTransformers
The Geometric Mechanics of Contrastive Representation Learning: Alignment Potentials, Entropic Dispersion, and Cross-Modal Divergence
Symmetries in language statistics shape the geometry of model representations
Robustness of Mixtures of Experts to Feature Noise
GXPO: Group Cross-Lingual Relative Policy Optimization for Code Generation
Revisiting the Volume Hypothesis
The Stability of Singular Distribution: A Spectral Perspective on the Two-Phase Dynamics of Language Model Pre-training
FRACTAL: State Space Model with Fractional Recurrent Architecture for Computational Temporal Analysis of Long Sequences
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
Improved Scaling Laws via Weak-to-Strong Generalization in Random Features Ridge Regression
Large Language Model Teaches Visual Students: Cross-Modality Transfer of Fine-Grained Conceptual Knowledge
Dissecting Quantization Error: A Concentration-Alignment Perspective
Infinite-Precision Autoregressive Modeling for Vector Graphics and Layouts
Improving Visual Token Reduction via Rectifying Distortions for Efficient Multimodal LLM Inference
Decoupled Training with Local Reinforcement Fine-Tuning in Federated Learning
Cognitive Fatigue in Autoregressive Transformers: Formalization and Measurement
LATMiX: Learnable Affine Transformations for Microscaling Quantization of LLMs
Order Matters: Unveiling the Hidden Impact of Macro Placement Sequences via Proxy-Guided LLM Evolution
On the Expressive Power of Permutation-Equivariant Weight-Space Networks
HieraMAS: Optimizing Intra-Node LLM Mixtures and Inter-Node Topology for Multi-Agent Systems
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
AnyMod-LLVE: Low-Light Video Enhancement with Modality-Agnostic Inference
Probing the Inductive Bias of Neural Networks through Learning Random Cellular Automata
Lie-Algebraic Neural Koopman Dynamics
Euler–Poincaré Neural Dynamics: A Geometric-Mechanics Framework for Scientific Simulation
Repositioning the Subject within Image
Position: Multiplicity is an Inevitable and Inherent Challenge in Multimodal Learning
Solving Inverse Problems with Flow-based Models via Model Predictive Control
CVSearch: Empowering Multimodal LLMs with Cognitive Visual Search for High-Resolution Image Perception
GemDepth: Geometry-Embedded Features for 3D-Consistent Video Depth
VividCam: Learning Unconventional Camera Motions from Virtual Synthetic Videos
Mixture of Distributions Matters: Dynamic Sparse Attention for Efficient Video Diffusion Transformers
VIP: Visual-guided Prompt Evolution for Efficient Dense Vision-Language Inference
FastSESR: Fast Scene-level Explicit Surface Reconstruction
RefChess: Monte-Carlo Move Selection for Zero-Shot Referring Image Segmentation
ObjEmbed: Towards Universal Multimodal Object Embeddings
PixCLIP: Towards Fine-grained Vision-Language Understanding via Any-granularity Pixel-Text Alignment
Diffeomorphism-Equivariant Neural Networks
SphericalDreamer: Generating Navigable Immersive 3D Worlds with Panorama Fusion
OpenGPT-4o-Image: A Comprehensive Dataset for Advanced Image Generation and Editing
G$^2$TAM: Geometry Grounded Track Anything Model
Task-Aware Mechanism: Hybrid MoE Vision Tower Towards Holistic Video Understanding
AmbiRefer3D: 3D Visual Grounding with Referential Ambiguity
CLIP Tricks You: Training-free Token Pruning for Efficient Pixel Grounding in Large Vision-Language Models
Spatially-Adaptive Gradient Re-parameterization for 3D Large Kernel Optimization
Position: Machine Learning for Heart Transplant Allocation Policy Optimization Should Account for Incentives
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
ProMiSE: Protein Multi-state Structure Evaluation Benchmark in Biological Contexts
UniMedVL: Unifying Medical Multimodal Understanding and Generation through Observation-Knowledge-Analysis
Bridging Dynamics and Data: A Unified Diffusion Framework for Mechanistically-Informed Epidemic Forecasting
Conditionally Site-Independent Neural Evolution of Antibody Sequences
Geometric Pocket-Centric Protein Encoding for Polypharmacology-Guided Multi-Target Drug Design
InfoGlobe: Local-and-Global Information-Preserving Statistical Manifold Learning for Single-Cell Transcriptomics
Object-level Semantic and Spatial Distillation for Open Vocabulary Detection
DC-W2S: Dual-Consensus Weak-to-Strong Training for Reliable Process Reward Modeling in Biological Reasoning
TD3B: Transition-Directed Discrete Diffusion for Allosteric Binder Generation
MoLF: Mixture-of-Latent-Flow for Pan-Cancer Spatial Gene Expression Prediction from Histology
SynerMedGen: Synergizing Medical Multimodal Understanding with Generation via Task Alignment
SP-Mind: An Autonomous Reasoning Agent for Spatial Proteomics Analysis
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
Token-Sparse Medical Multimodal Reasoning via Dual-Stream Reinforcement Learning
Med-Scout: Curing MLLMs' Geometric Blindness in Medical Perception via Geometry-Aware RL Post-Training
DeCoDe: Decoupling Binding Position and Molecular Conformation in 3D Ligand Diffusion for Structure-Based Drug Design
Preference-based Antibody Expression Ranking: Scaling with Large-scale Weak Supervision
COFT: Counterfactual–Conformal Decoding for Fair Chain‑of‑Thought Reasoning in Large Language Models
Beyond Independent Genes: Learning Module-Inductive Representations for Gene Perturbation Prediction
Discrete Diffusion with Physical Mass Constraints for \emph{De Novo} Peptide Sequencing
Influence-Guided Symbolic Regression: Scientific Discovery via LLM-Driven Equation Search with Granular Feedback
Dual-View Predictive Diffusion: Lightweight Speech Enhancement via Spectrogram-Image Synergy
Neural-Inspired Modeling of Auditory Selection and Compensation for Audio-Visual Speech Separation
How Far Can LLM Agents Reason with Tables? Benchmarking Multi-Turn Agentic Table Question Answering in the Wild
SAM Audio: Segment Anything in Audio
S3Audio: Towards Streaming Synchronized Spatial Audio Generation via Autoregressive Diffusion Transformer
Toward Robust Multilingual Adaptation of LLMs for Low-Resource Languages
PosterAgent: Agentic Poster Generation via Stage-Aware Reinforcement Learning
NaviAgent: Graph‑Driven Bilevel Planning for Scalable Tool Orchestration
ConsMSA: Semantic Distribution Consistency Learning for Multimodal Sentiment Analysis
Group Cognition Learning: Making Everything Better Through Controlled Two-Stage Agents Collaboration
Do Audio LLMs Listen or Read? Analyzing and Mitigating Paralinguistic Failures with VoxParadox
CoCoEmo: Composable and Controllable Human-Like Emotional TTS via Activation Steering
OMP: One-step Meanflow Policy with Directional Alignment
Position: Predicting AI’s Impact on Labor Is a Core Machine Learning Problem
Position: Time to Close The Validation Gap in LLM Social Simulations
Discovering Differences in Strategic Behavior between Humans and LLMs
CollabBench: Benchmarking and Unleashing Collaborative Ability of LLMs with Diverse Players via Proactive Engagement
GeoFlow: Geo-Aware Modeling of Inter-Area Relationships in OD Flow Prediction and Generation
AgentSelect: Benchmark for Narrative Query-to-Agent Recommendation
Grounded in Reality: Learning and Deploying Proactive LLM from Offline Logs
When Data Is Scarce: Scaling Sparse Language Models with Repeated Training
MEnvAgent: Scalable Polyglot Environment Construction for Verifiable Software Engineering
Optimal Pricing for Data-Augmented AutoML Marketplaces
HECTOR: Hybrid Editable Compositional Object References for Video Generation
InteractScience: Programmatic and Visually-Grounded Evaluation of Interactive Scientific Demonstration Code Generation
JADE: Expert-Grounded Dynamic Evaluation for Open-Ended Professional Tasks
Improving ML attacks on LWE with data repetition and stepwise regression
SD-MoE: Spectral Decomposition for Effective Expert Specialization
CALM Before the STORM: Unlocking Native Reasoning for Optimization Modeling
AOEB: Benchmarking Agent-Oriented Multimodal Embeddings
HumanLM: Simulating Users with State Alignment Beats Response Imitation
PRPO: Paragraph-level Policy Optimization for Vision-Language Deepfake Detection
ResRL: Boosting LLM Reasoning via Negative Sample Projection Residual Reinforcement Learning
Reward Learning through Ranking Mean Squared Error
The Hippocampal Place Field Gradient: A Bio-inspired Framework Building Multiscale Representation for Better Sample Efficiency
Provably Efficient Policy-Reward Co-Pretraining for Adversarial Imitation Learning
Towards Understanding Adam Convergence on Highly Degenerate Polynomials
Noise-Guided Transport: Imitation Learning from Random Priors
TimeRewarder: Learning Dense Reward from Passive Videos via Frame-wise Temporal Distance
BuildArena: A Physics‑Aligned Interactive Benchmark of LLMs for Engineering Construction
Population-Aware Imitation Learning in Mean-field Games with Common Noise
Generative Online Reinforcement Learning
COLLIE: Guiding Skill Discovery in Semantically Coherent Latent Space
Towards Understanding Continual Factual Knowledge Acquisition of Language Models: From Theory to Algorithm
Squeezing More from the Stream : Learning Representation Online for Streaming Reinforcement Learning
MPFM: Cross Multi-Domain Prototype Flow Matching for Log Anomaly Detection
Mirror Descent Actor Critic via Bounded Advantage Learning
Geometric Coherence Learning for Structuring Value Functions in Plain MDPs
POLIA: Policy Optimization with Visual-Object-Level Intrinsic Advantage for Multimodal Reasoning
Noise-corrected GRPO: From Noisy Rewards to Unbiased Gradients
Flow Inverse Reinforcement Learning
Beyond Token-level Supervision: Unlocking the Potential of Decoding-based Regression via Reinforcement Learning
Position: Agent Security Needs Redefinition through a Holistic Framework
Position: Adversarial ML for LLMs Is Not Making Any Progress
Position: LLMs can't jump
Decoupled Low-Rank Adaptation for Robust Federated Fine-Tuning
Great Minds Think Alike: Contextual Tacit Communication for Decentralized LLM-Agent Cooperation
$G^2$-Reader: Dual Evolving Graphs for Multimodal Document QA
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
Test-Time Guidance for Flow-Based Generative Models via Parallel Tempering on Source Distributions
Towards Robust Human-AI Complementarity under Uncertainty
PRISM: Perception Reasoning Interleaved for Sequential Decision Making.
FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs
Generalization Bounds for Out-of-distribution Generalization
Calibrated Multimodal Representation Learning with Missing Modalities
Faithful Relational Reasoning with Region-based Embeddings: Expressivity of Convex Coordinate-wise Models
Agentic Confidence Calibration
Memory Caching: RNNs with Growing Memory
Scalable Single-Cell Gene Expression Generation with Latent Diffusion Models
Architecture Matters for Multi-Agent Security
HEDP: A Hybrid Energy-Distance Prompt-based Framework for Domain Incremental Learning
LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation
Predicting evolutionary rate as a pretraining task improves genome language model representations
Generative Modeling of Discrete Latent Structures via Dynamic Policy Gradients
Principled SVD-based Delta Compression via Quantization Error Minimization
Two Modalities Are Better Than One: Efficient Adversarial Purification via Multimodal Diffusion Models
Experience Augmented Policy Optimization for LLM Reasoning
FPTQuant: Function-Preserving Transforms for LLM Quantization
Ego3S: Select, Strengthen, and Synchronize for Efficient Egocentric Reasoning
Text Has Curvature
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
Training-Free Distribution Adaptation for Diffusion Models via Maximum Mean Discrepancy Guidance
Beyond Policy Training: Recursive Solution Search from Unannotated Videos
TopAdapter: Topology-Aware Prompt Tuning for Efficient Point Cloud Understanding
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
Position: Certified Correctness in Neural Constraint Reasoning Requires Symbolic Integration
MUSE: Resolving Manifold Misalignment in Visual Tokenization via Topological Orthogonality
Unveiling And Addressing Dimensional Collapse In Vector Quantization Models Via Codebook Regularization
MASPO: Joint Prompt Optimization for LLM-based Multi-Agent Systems
Scaling Transformers for End-to-End Discrete Audio Tokenization
Beyond Majority Voting: Self-Reflective Test-Time Reinforcement Learning for LLM Reasoning
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
Stabilizing Recurrent Dynamics for Test-Time Scalable Latent Reasoning in Looped Language Models
Knapsack RL: Unlocking Exploration of LLMs via Optimizing Budget Allocation
From Generalist to Specialist Representation
LangForce: Bayesian Decomposition of Vision Language Action Models via Latent Action Queries
Hermes: An Evidence-Driven Agentic Framework for Trustworthy and Explainable AI-Generated Video Detection
Position: Unlabeled ≠ No Human Supervision in Visual Learning
Position: *Beyond Text* The Text-Centric Bias in Foundation Models Must Be Revisited for a Speech-First Future
DC-Leap: Training-Free Acceleration of dLLMs via Draft-Guided Contiguous Leaping Decoding
NorMuon: Making Muon more efficient and scalable
KFStego: Key-Free Secure Image Distribution via Bipartite Structural Invariants
When Random Saliency Looks Trained: Architectural Center Bias in CNN Interpretability
Position: Assistive AI requires Personalized Specialists, not Generalists
Addressing Semantic Blind Spots in Text-to-SQL via Component Pre-generation and AST Matching Rewards
Diffusing to Coordinate: Efficient Online Multi-Agent Diffusion Policies
Rank-Aware Spectral Bounds on Attention Logits for Stable Low-Precision Training
Position: Prioritize Identifying Structure, Not Complex Models, for Scientific Discovery
Synthesizing world models for bilevel planning
NeurIPS: Neuro-anatomical Inductive Priors for Sphere-based Brain Decoding
Letting Trajectories Spread: Quality-Preserving Control for Diverse Flow Matching
Position: Ideas Should be the Center of Machine Learning Research
EigenCache: Rethinking Diffusion Acceleration as Covariance-Optimal Forecasting and Submodular Information Allocation
Position: Age Estimation Models Do Not Process Biometric Data
Rethink the Role of Neural Decoders in Quantum Error Correction
Biased Generalization in Diffusion Models
Position: Model identity in machine learning is a convention, not a property
PDAgent: An LLM-Driven Autonomous Agent Framework Towards *In Silico* Protein Design via Directed Mutation
Position: Sycophancy is an Educational Safety Risk: Why LLM Tutors Need Sycophancy Benchmarks
AdvEvo-MARL: Shaping Internalized Safety through Adversarial Co-Evolution in Multi-Agent Reinforcement Learning
Mitigating Per-Sample Harm in Stochastic Optimization
STD-Former: Image-Conditioned Texture Dictionary Encoding with Sparse Topological Supervision for Texture Recognition
Does Reasoning Improve Seeing? Understanding When Vision-Language Models Benefit from Thinking
End-to-End Compression for Tabular Foundation Models
TRACER: Persistent Regularization for Robust Multimodal Finetuning
Position: AI Must Become Planet-Centered, Not Human-Centered
Watermarking Graph Neural Networks via Explanations for Ownership Protection
Position: LLM Benchmark Datasets should be Contamination-Resistant
Tackling Fake Forgetting through Uncertainty Quantification
Transforming Weather Data from Pixel to Latent Space
Exploring Nonlinear Pathway in Parameter Space for Machine Unlearning
Unlocking Cross-Modal Biosignal Synthesis: A Temporally-Aware VAE-Diffusion Model
Position: We Need AI Efficiency Incentives for Accessibility and Sustainability
Mem-T: Densifying Rewards for Long-Horizon Memory Agents
Position: AI Capabilities Are Not Increasing Exponentially
Adaptive Policy Backbone via Shared Network
SFCLTA: Spectral Fusion Contrastive Learning with Topology-Adaptive Graph Augmentation
Causal discovery for time series with endogenous context variables
Position: Metaphysical Concepts in AI Should Be Judged by Their Consequences
Identifying Latent Concepts and Structures for Generalized Category Discovery
Beyond Literal Translation: Evaluating Cultural Effectiveness in Social Media UGC
AlgoVeri: An Aligned Benchmark for Verified Code Generation on Classical Algorithms
Reliable Neighborhood-Aware Multi-View Outlier Detection
Position: Good Embodied Reward Models Need Bad Behavior Data
Position: Generative Distributional Integrity against Backdoor Attacks
3ViewSense: Spatial and Mental Perspective Reasoning from Orthographic Views in Vision-Language Models
Gradient-Free Approaches is a Key to an Efficient Interaction with Markovian Stochasticity
Unsupervised Hierarchical Skill Discovery
Interpretable Functional Koopman Learning with Non-Markovian Closure for Spatiotemporal Systems
Optimization Dynamics of Equivariant and Augmented Neural Networks
ReQAT: Achieving Full-Precision Reasoning Accuracy with 4-bit Floating-Point Quantization-Aware Training
“very likely” Means “uncertain”? How LLMs Diverge from Humans in Linguistic Uncertainty Quantification
(Be Cautious!) Bio-Foundation Models Are Not Yet Robust to Biologically Plausible Perturbations and ML Transformations
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
Klein Hyperbolic Metric Learning
Interpretable Embeddings with Sparse Autoencoders: A Data Analysis Toolkit
Improving 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
Restoring Exploration after Post-Training: Latent Exploration Decoding for Large Reasoning Models
Causal Matrix Completion under Multiple Treatments via Mixed Synthetic Nearest Neighbors
PanoWorld-X: Generating Explorable Panoramic Worlds via Sphere-Aware Video Diffusion
GameDevBench: Evaluating Agentic Capabilities Through Game Development
LagLLM: LLM-empowered lead–lag dependency learning for spatial-temporal time series forecasting
Second-Order Smooth Planning with Optimal-Transport Bellman Smoothing
DV-World: Benchmarking Data Visualization Agents in Real-World Scenarios
INDUCTION: Finite-Structure Concept Synthesis in First-Order Logic
Sharpness-Aware Pretraining Mitigates Catastrophic Forgetting
Building Social World Model with Large Language Models
Understanding Deep Representation Learning via Layerwise Feature Compression and Discrimination
Efficient and Minimax-optimal In-context Nonparametric Regression with Transformers
Provably Label-Efficient Conformal Prediction
Scaling Laws for Precision in High-Dimensional Linear Regression
All ERMs Can Fail in Stochastic Convex Optimization Lower Bounds in Linear Dimension
Pressure Reveals Character: Behavioural Alignment Evaluation at Depth
ScoreMatchingRiesz: Score Matching for Debiased Machine Learning and Policy Path Estimation
Position: Quantum Deep Learning Still Needs a Quantum Leap
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
HOBIT: Hardness Optimized Batch Sampling for InfoNCE Training
Rethinking Feature Alignment in Generalist Graph Anomaly Detection: A Relational Fingerprint-based Approach
Learning GUI Grounding with Spatial Reasoning from Visual Feedback
MIRA: A Score for Conditional Distribution Accuracy and Model Comparison
Regression Language Models for Code
Divergence Decoding: Targeted Unlearning via Auxiliary Models
Anchored Policy Optimization: Mitigating Exploration Collapse via Support-Constrained Rectification
$\texttt{PRISM}$: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
Model Fusion via Retrofitting
Learning to Approximate Uniform Facility Location via Graph Neural Networks
No Data? No Problem: Robust Vision-Tabular Learning with Missing Values
Measuring and Mitigating Post-hoc Rationalization in Reverse Chain-of-Thought Generation
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
Trust3R: Unifying Feed-Forward Pointmap Prediction and Evidential Learning for Trust-Aware 3D Reconstruction
Language Generation with Feedback: Queries and Mistakes
Learning-Augmented Online Covering Problems
A Theory of Data Acquisition and Pricing at Scale
From Generative to Episodic: Sample-Efficient Replicable RL
Human-AI Collaborative Uncertainty Quantification
A Statistical Framework for Analyzing Specification Resistance to Learnware-Inversion Risks
Causal Identification from Counterfactual Data: Completeness and Bounding Results
Biases in the Blind Spot: Detecting What LLMs Fail to Mention
Automatically Finding Reward Model Biases
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
Fast and Optimal Algorithms for Private Hypothesis Selection
CrossQ: Task-Aligned Cross-Token Conditional Quantization for Late Interaction Retrieval
Position: Stop evaluating AI with human tests, develop principled, AI-specific tests instead
Position: AI Researchers Must Lead Arms Control to Mitigate Military AI Risks
Scaling Inference-Time Computation via Opponent Simulation: Enabling Online Strategic Adaptation in Repeated Negotiation
Position: Accountable Deployment of Agentic AI Demands Layered, System-Level Interpretability
Position: Let’s Build a Trustworthy Model Context Protocol!
Position: AI Leaderboards Are Underserving the Global South: A Case Study from India
Optimal Fair Aggregation of Crowdsourced Noisy Labels using Demographic Parity Constraints
Text-Conditional JEPA for Learning Semantically Rich Visual Representations
Online Social Welfare Function-based Resource Allocation
When Do Hallucinations Arise? A Graph Perspective on the Evolution of Path Reuse and Path Compression
Position: Knowing Isn’t Understanding: Re-grounding Generative Proactivity with Epistemic and Behavioral Insight
Position: Deployed Reinforcement Learning should be Continual
Understanding Truncated Positional Encodings for Graph Neural Networks
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
Edge-colored Clustering in Hypergraphs: A MaxECC Approximation
Rethinking Contrastive Learning for Graph Collaborative Filtering: Limitations and A Simple Remedy
QEDBench: Quantifying the Alignment Gap in Automated Evaluation of University-Level Mathematical Proofs
Implicit Intelligence - Evaluating Agents on What Users Don’t Say
Syntax vs. Semantics: How Transformers Learn Deep Dependencies
Proximal-IMH: Proximal Posterior Proposals for Independent Metropolis–Hastings with Approximate Operators
MET-Bench: Multimodal Entity Tracking for Evaluating the Limitations of Vision-Language and Reasoning Models
Strategic Candidacy in Generative AI Arenas
MIDSTEER: Optimal Affine Framework for Steering Generative Models
Influence-Disentangled Federated Training: Learning Models That Are Easy to Unlearn
FlowSeg: Dynamic Semantic Guidance for LLM-Conditioned Segmentation
$\tau$-Knowledge: Evaluating Conversational Agents over Unstructured Knowledge
Learning Anisotropic Value Geometry with Finsler Reinforcement Learning
Long Grounded Thoughts: Synthesizing Grounded Visual Problems and Distilling Reasoning Chains at Scale
Behavior-Invariant Task Representation Learning with Transformer-based World Models for Offline Meta-Reinforcement Learning
World Guidance: World Modeling in Condition Space for Action Generation
MARS: Modular Agent with Reflective Search for Automated AI Research
Adaptive Recurrent Message Passing for Test Time Computing on Graphs
Beyond Rational Illusion: Behaviorally Realistic Strategic Classification
Online Compatible Reward Identification from Preference Feedback
QuITE: Query-based Irregular Time-series Embedding
When Tabular Foundation Models Meet Strategic Tabular Data: A Prior Alignment Approach
Unveiling Prior-data Fitted Networks on Causal Effect Estimation: Pre-training or Finetuning?
FactGuard: Agentic Video Misinformation Detection via Reinforcement Learning
Probabilistic Salient Object Ranking
Stratified GRPO: Handling Structural Heterogeneity in Reinforcement Learning of LLM Search Agents
Efficient privacy loss accounting for subsampling and random allocation
RL4RLA: Teaching ML to Discover Randomized Linear Algebra Algorithms through Curriculum Design and Graph-based Search
MaxSAT-Based Compression for Tsetlin Machines
MFH-NAS:A Hybrid Neural Architecture Search Framework for Multimodal Fusion Object Detection
The Power of Power Law: Asymmetry Enables Compositional Reasoning
Streaming Sliced Optimal Transport
Corrigibility Transformation: Constructing Goals That Accept Updates
A Behavioural and Representational Evaluation of Goal-Directedness in Language Model Agents
Black-Box Assisted Regression: Phase Transitions and Minimax Optimality
TFTF: Training-Free Targeted Flow for Conditional Sampling
Deep Networks Learn Deep Hierarchical Models
Skipping the Zeros in Diffusion Models for Sparse Data Generation
DexMachina: Functional Retargeting for Bimanual Dexterous Manipulation
Score-Repellent Monte Carlo: Toward Efficient Non-Markovian Sampler with Constant Memory in General State Spaces
Bregman meets Lévy: Stochastic Mirror Descent with Heavy-Tailed Noise in Continuous and Discrete Time
PepCompass: Navigating Peptide Embedding Spaces Using Riemannian Geometry
Dimension-free convergence of diffusion models for approximate Gaussian mixtures
Local Mechanisms of Compositional Generalization
Beyond First-order Asymptotics in Sequential Mean Testing
SC$^{2}$-WM: A Self-Correcting World Model with Closed-Loop Feedback for Vision-and-Language Navigation in Continuous Environments
Consistent Diffusion Language Models
Spatial Conformal Inference through Localized Quantile Regression
Near-Optimal Convergence of Accelerated Gradient Methods under Generalized and $(L_0,L_1)$-Smoothness
Bilevel Optimization over Saddle Points of Zero-Sum Markov Games
Generalization of Gibbs and Langevin Monte Carlo Algorithms in the Interpolation Regime
Reduction of Probabilistic Chemical Reaction Networks
Neutral-Reference Prompting for Vision–Language Models
Success-Conditioning as Policy Improvement: The Optimization Problem Solved by Imitating Success
Graph of States: Solving Abductive Tasks with Large Language Models
Prior Diffusiveness and Regret in the Linear-Gaussian Bandit
How high is ‘high’? Rethinking the roles of dimensionality in topological data analysis and manifold learning
Who can we trust? LLM-as-a-jury for Comparative Assessment
Probabilistic Pretraining for Improved Neural Regression
Generalization Bounds for Discrete Diffusion: Statistical Advantage of Masking
Improved Convergence of Score-Based Diffusion Models via Prediction-Correction
On the Convergence of Adaptive Gradient Methods for Nonconvex Optimization
Expert Routing with Synthetic Data for Domain Incremental Learning
UCB Exploration for Fixed-Budget Bayesian Best Arm Identification
Physics-Aware Spatiotemporal Causal Graph Network for Forecasting with Limited Data
Zono-Conformal Prediction: Zonotope-Based Uncertainty Quantification for Regression and Classification Tasks
Position: No Retroactive Cure for Infringement during Training
Position: AGI Requires a Coordination Layer on Top of Pattern Repositories
PolicyGuard: Towards Test-time and Step-level Backdoor Defense for Reinforcement Learning Agent
Position: The Case for Theory-Level Autoformalization
Position: It’s Time to Optimize for Self-Consistency
Position: Significant impact of numerical precision in scientific machine learning
Position: Regulating Algorithms Is Not Enough. A Study of Content Discovery in Online Platforms
Position: Explainability Research Must Prioritize Foundations over Ad-hoc Methods
Compositional Generative Modeling from Decentralized Data
FUSE: Quantifying Uncertainty in Multimodal LLMs by Bayesian Fusing Epistemic and Aleatoric Uncertainty
Position: Web Agents Should Use Typed Actions Instead of Click-Based Browsing
Position: EU AI Act's Research Exemptions Can Break the Publication Norms of Major AI Conferences
Position: Comprehensive AI governance requires addressing non-model capability gains
Position: Reframing Hallucination: Latent Space Geodesics as a Pathway for Generative Discovery
Position: Interpretability in Deep Time Series Models Demands Semantic Alignment
Position: The Data Provenance–Parametric Divide in Large Language Models
Position: Your VLM May Not Be Thinking with Interleaved Images
Position: ICML Should Treat Hosted LLM APIs as Versioned Dependencies and Require Drift-Audit Artifacts
Position: Stop Anthropomorphizing Intermediate Tokens as Reasoning/Thinking Traces!
Position: LLM-Safety Evaluations Lack Robustness
Position: Reliable AI Needs to Externalize Implicit Knowledge: A Human–AI Collaboration Perspective
Position: Responsible AI for AI companions must actively combat violence toward intimate partners
Position: Use Sparse Autoencoders to Discover Unknowns
Position: LLM Serving Needs Mathematical Optimization and Algorithmic Foundations, Not Just Heuristics
UnMaskFork: Test-Time Scaling for Masked Diffusion via Deterministic Action Branching
Low-Compute Watermark Removal via Dual-Domain Natural Projection
Mind Your Entropy: From Maximum Entropy to Trajectory Entropy-Constrained RL
Steer Like the LLM: Activation Steering that Mimics Prompting
Introspection Adapters: Training LLMs to Report Their Learned Behaviors
Beyond Looking Up, Try Looking Around: Harmonizing Global Structure and Local Consistency in Optimal Transport for Short Text Clustering
Online Contract Design With Unknown Technology
Cross-Tactile Sensor Representation Learning
Reflective Hamiltonian Monte Carlo: Mixing Analysis and Application to Sampling on Stiefel Manifold
Amortized Maximum Inner Product Search with Learned Support Functions
Language Bias in LVLMs: From In-Depth Analysis to Simple and Effective Mitigation
Computational Arbitrage in AI Model Markets
SLQ: Bridging Modalities via Shared Latent Queries for Retrieval with Frozen MLLMs
Quantifying Frontier LLM Capabilities for Container Sandbox Escape
Towards Functional Correctness of Large Code Models with Selective Generation
ABSINT-AI: Agentic Heap Abstractions for Abstract Interpretation
DirectEdit: Step-Level Accurate Inversion for Flow-Based Image Editing
Non-Adversarial Imitation Learning Provably Free of Compounding Errors: The Role of Bellman Constraints
Refining Dual Spectral Sparsity in Transformed Tensor Singular Values
Generation is Required for Data-Efficient Perception
Vision Language Models Cannot Reason About Physical Transformation
LOTTERY: Learning from Reference-Only Samples in Two-Sample Testing under Size Asymmetry
Understanding Transfer Learning of RNA Foundation Models on Downstream Tasks
A Fine-Grained Understanding of Uniform Convergence for Halfspaces
Why Are Linear RNNs More Parallelizable?
Information Geometry Loss for Time Series Forecasting
TINNs: Time-Induced Neural Networks for Solving Time-Dependent PDEs
Hyper-LLaVA: Hyperbolic Uncertainty-aware Modality-Balanced Routing for Multimodal Continual Instruction Tuning
Break the Block: Dynamic-size Reasoning Blocks for Diffusion Large Language Models via Monotonic Entropy Descent with Reinforcement Learning
Towards Efficient LLMs Annealing with Principled Sample Selection
Op-CAD: Benchmarking and Investigating Operation-oriented CAD Generation
Beyond Logits: Metastable Latent Dynamics for Sample-Efficient Best-of-N Selection in LLMs
Keep Everyone Happy: Online Fair Division of Numerous Items with Few Copies
XSpecMesh: Quality-Preserving Auto-Regressive Mesh Generation Acceleration via Multi-Head Speculative Decoding
Rethinking KV Cache Eviction via a Unified Information-Theoretic Objective
A Sketch-and-Project Analysis of Subsampled Natural Gradient Algorithms
A Penalty Approach For Differentiation Through Black-box Quadratic Programming Solvers
Cello: A Universal Cell-wise Feature Aggregation framework for Reliable Pathology Images Analysis
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
TopBench: A Benchmark for Implicit Prediction and Reasoning over Tabular Question Answering
SG2Loc: Sequential Visual Localization on 3D Scene Graphs
LocalV: Exploiting Information Locality for IP-level Verilog Generation
On Contraction of Sequential and Offset Rademacher Complexities
Learning to Label: A Reinforced Self-Evolving Framework for Semi-supervised Referring Expression Segmentation
Distilling Task-Level Coordination Policies for Generalizable Multi-Agent Cooperation
SL-VC: A Benchmark and Automated Framework for Separation Logic Verification Condition Proving
Quantifying the Generalization Gap in Seizure Detection: A Large-Scale Empirical Benchmark via the SzCORE Challenge
OptiFluence: Principled Design of Privacy Canaries
Robust and Consistent Ski Rental with Distributional Advice
Adversarial Training for Process Reward Models
ExpWeaver: LLM Agents Learn from Experience via Latent RAG
Esoteric Language Models
ScaleEnv: Scaling Environment Synthesis from Scratch for Generalist Interactive Tool-Use Agent Training
MGAL: A Multilingual Granularity-Aware Long-Context Benchmark
Modality-Decoupled Online Recursive Editing
MoshiRAG: Asynchronous Knowledge Retrieval for Full-Duplex Speech Language Models
SAOT: Self-Supervised Continual Graph Learning with Structure-Aware Optimal Transport
CLIMB: Taming the LoRA Residency Cliff in Multi-LoRA Serving
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
Semi-Supervised Neural Super-Resolution for Mesh-Based Simulations
DIVE: Scaling Diversity in Agentic Task Synthesis for Generalizable Tool Use
KernelFoundry: Hardware-Aware Evolutionary GPU Kernel Optimization
SPA: A Simple but Tough-to-Beat Baseline for Knowledge Injection
Predicting the Emergence of Induction Heads in Language Model Pretraining
From Evaluation to Design: Using Potential Energy Surface Smoothness Metrics to Guide ML Interatomic Potential Architectures
Equilibrium Propagation for Non-Conservative Systems
Learn to change the world: Multi-level reinforcement learning with model-changing actions
SpecExit: Accelerating Large Reasoning Model via Speculative Exit
Adaptively Robust Resettable Streaming
Skill Neologisms: Towards Skill-based Continual Learning
Improved Algorithms for Nash Welfare in Linear Bandits
Learning to Think in Physics: Breaking Shortcut Learning in Scientific Diffusion via Representation Alignment
Training-Free Adaptation of Diffusion Models via Doob's $h$-Transform
Transform Trained Transformer for Accelerating Native 4K Video Generation
GUDA: Counterfactual Group-wise Training Data Attribution for Diffusion Models via Unlearning
Adaptive Estimation and Inference in Semi-parametric Heterogeneous Clustered Multitask Learning via Neyman Orthogonality
TSFAdv: Frequency-Guided Black-Box Adversarial Attacks on Time Series Forecasting
Causes and Consequences of Representational Similarity in Machine Learning 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
MLUBench: A Benchmark for Lifelong Unlearning Evaluation in MLLMs
Learning Adaptive Topology with FiLM-Guided Distillation for Tertiary Structure-Based RNA Design
Personalized Policy Learning through Discrete Experimentation
When AI Agents Compete for Jobs: Strategic Capabilities and Economic Dynamics of AI Labour Markets
Learning Global Representation from Queries for Vectorized HD Map Construction
Variance-Reduced $(\varepsilon, \delta)-$Unlearning using Forget Set Gradients
Training Prompt Matters: State-Adaptive Optimization for Robust Fine-Tuning
Approximating f -Divergences with Rank Statistics
Auditing Sybil: Explaining Deep Lung Cancer Risk Prediction Through Generative Interventional Attributions
Uncovering the Latent Potential of Deep Intermediate Representations
OCNR: Stabilizing Self-Play by Mitigating Iteration-Collapse With One-Class Novelty Rewards
FedUSD: Unbiased Synthetic Data for Federated Learning
Algorithmic Recourse of In-Context Learning for Tabular Data
Evaluating Parameter Efficient Methods for RLVR
Learn from A Rationalist: Distilling Intermediate Interpretable Rationales
RedDebate: Safer Responses Through Multi-Agent Red Teaming Debates
RECTOR: Masked Region-Channel-Temporal Modeling for Affective and Cognitive Representation Learning
Safety Game: Inference-Time Alignment of Black-Box LLMs via Constrained Optimization
$\mathbb{R}^{2k}$ is Theoretically Large Enough for Embedding-based Top-$k$ Retrieval
Federated Bilevel Performative Prediction
Mixtures of geodesic factor analyzers on Riemannian homogeneous spaces
Token-Efficient Change Detection in LLM APIs
IVQA-LD: Inclusive Multimodal Understanding for Population with Limb-Deficiency
FaPS: A General and Fast Training Method for Diffusion Models
Sharpness-Aware Minimization Can Hallucinate Minimizers
Unpaired Visual Editing with Self-Consistent Flow Matching
Projected Gradient Ascent for Efficient Reward-Guided Updates with One-Step Generative Models
Simple Policy Gradients for Reasoning with Diffusion Language Models
How Language Models Process Negation
Asymptotically Fast Clebsch-Gordan Tensor Products with Vector Spherical Harmonics
Stem: Rethinking Causal Information Flow in Sparse Attention
Rethinking Attention in Spiking Transformers: Overcoming Density Bias with Set Similarity
TD-VAD: Breaking Visual Dependence in Video Anomaly Detection with Text-Driven Learning
What If We Let Forecasting Forget? A Sparse Bottleneck for Cross-Variable Dependencies
DuRP: Dual-Stage Physics-Embedded Learning for Joint Radiance and Polarization Restoration
Capacitated Fair-Range Clustering: Hardness and Approximation Algorithms
REVIS: Sparse Latent Steering to Mitigate Object Hallucination in Large Vision-Language Models
RVAS: Referring Video Active Exploration and Segmentation
Learning to Discover at Test Time
Autoregressive Language Models are Secretly Energy-Based Models: Insights into the Lookahead Capabilities of Next-Token Prediction
Training-Free Multimodal Large Language Model Orchestration
When and How Human Curation Backfires: Preference Alignment under Multi-Model Self-Consuming Loop
Thinking in Flow: A Dissipative Stabilization Operator for Robust Autoregressive Reasoning
Maximin Relative Improvement: Fair Learning as a Bargaining Problem
Spherical Steering: Geometry-Aware Activation Rotation for Language Models
S$^3$GNN: Efficient Global Mixing and Local Message Passing for Long-Range Graph Learning
Riemannian Optimization for Fair Spectral Clustering
Monitorability as a Free Gift: How RLVR Spontaneously Aligns Reasoning
Very Efficient Listwise Multimodal Reranking for Long Documents
Understanding Behavior Cloning with Action Quantization
Resilient Coresets and Consistent Clustering
MASPOB: Bandit-Based Prompt Optimization for Multi-Agent Systems with Graph Neural Networks
Minibatch Optimal Transport and Perplexity Bound Estimation in Discrete Flow Matching
Align Your Trajectory Tangent: Training Better Consistency Models via Manifold-Aligned Tangents
On Testing Conditional Mean Independence for Manifold-Valued Data
Message Tuning Outshines Graph Prompt Tuning: A Prismatic Space Perspective
Weight-Space Learning for Certifiable Few-shot Transfer Learning
On Robustness and Chain-of-Thought Consistency of RL-Finetuned VLMs
From Retrieval to Translation: Translating Query into Graph-level Clues for Retrieval-Augmented Generation
Respecting Modality Gap in Post-hoc Out-of-distribution Detection with Pre-trained Vision-Language Models
Beyond ReLU: Bifurcation, Oversmoothing, and Topological Priors
Reward and Guidance through Rubrics: Promoting Exploration to Improve Multi-Domain Reasoning
Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers
Learning Realistic Depth via Physics-Grounded Noise Disentanglement with Semantic-Geometric Collaboration
A Unified Approach to Interpreting Knowledge Distillation for Large Language Models via Interactions
Identifying Connectivity Distributions from Neural Dynamics Using Flows
The Viscosity of Logic: Phase Transitions and Hysteresis in DPO Alignment
Local Intrinsic Dimension of Representations Predicts Alignment and Generalization in AI Models and Human Brain
LERD: Latent Event-Relational Dynamics for Neurodegenerative Classification
Conformal Risk-Averse Decision Making with Action Conditional Guarantee
Pessimistic Verification for Open-Ended Math Questions
See, Act, Adapt: Active Perception for Unsupervised Cross-Domain Visual Adaptation via Personalized VLM-Guided Agent
HybridOM: Hybrid Physics-Based and Data-Driven Global Ocean Modeling with Efficient Regional Downscaling
Train for Truth, Keep the Skills: Binary Retrieval-Augmented Reward Mitigates Hallucinations
FairMerging: Rethinking Model Merging through the Lens of Fairness
Enhancing LLMs for Graph Tasks via Graph-aware LoRA Generation
Membership Inference Attacks for Unseen Classes
Gradient Flow Through Diagram Expansions: Learning Regimes and Explicit Solutions
MotionMAR: Multi-scale Auto-Regressive Human Motion Reconstruction from Sparse Observations
Joint-Embedding Predictive Learning of Latent Market States in U.S. Equities
Risk-Averse and Optimistic Advertiser Incentive Compatibility in Auto-bidding
CVE-Factory: Scaling Expert-Level Agentic Tasks for Code Security Vulnerability
$\text{DT}^\text{2}$: Decision-Targeted Digital Twins
Prism-MoE: Efficient Dense-to-MoE Conversion for Visual Autoregressive Generation
Hyperbolic RQ-VAE enhanced Generative Recommendation with Differential-Length Codebook Strategy
CoCoQuant: Breaking the Bandwidth Wall via Co-Optimized Communication and Computation Quantization
Interventional Processes For Causal Uncertainty Quantification
UrbanFusion: Stochastic Multimodal Fusion for Contrastive Learning of Robust Spatial Representations
Geometric Conformal Prediction with Spatial Ranks and Multivariate Quantiles
Solving Imperfect-Recall Games via Sum-of-Squares Optimization
AutoTool: Dynamic Tool Selection and Integration for Agentic Reasoning
Normalization Equivariance for Arbitrary Backbones, with Application to Image Denoising
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
Deep sequence models tend to memorize geometrically; it is unclear why.
Predicting What Matters: Robust Generalist Robot Policy Learning via Future Semantic Mask
Correcting Overparameterization Effects in Fair Empirical Risk Minimization
PLASH: Provably Linear-Time Attention with Selective Higher-Order Feature Sketching
InfVSR: Toward Consistency-Driven Streaming Generative Video Super-Resolution
Spatiotemporal Imputation with Graph-Informed Flow Matching
Data- and Variance-dependent Regret Bounds for Online Tabular MDPs
Learning to Search and Searching to Learn for Generalization in Planning
Formally Exploring Visual Anomaly Detection Evaluation Metrics
CARE: Class-Adaptive Expert Consensus for Reliable Learning with Long-Tailed Noisy Labels
Stochastic Order Learning: An Approach to Rank Estimation Using Noisy Data
Factored Causal Representation Learning for Robust Reward Modeling in RLHF
Optimal and Scalable MAPF via Multi-Marginal Optimal Transport and Schrödinger Bridges
CoCoReviewBench: A Completeness- and Correctness-Oriented Benchmark for AI Reviewers
DiP-G: Discrete Prompting for Graph Neural Networks
PrivCode++ : Latent-Conditioned Differentially Private Code Generation for Comprehensive Guarantees
Conflict-Aware Additive Guidance for Flow Models under Compositional Rewards
Transolver-3: Scaling Up Transformer Solvers to Industrial-Scale Geometries
ASRU: Activation Steering Meets Reinforcement Unlearning for Multimodal Large Language Models
Swordsman: Entropy-Driven Adaptive Block Partition for Efficient Diffusion Language Models
Are VLMs Seeing or Just Saying? Uncovering the Illusion of Visual Re-examination
Generative Inverse Design with Abstention via Diagonal Flow Matching
Positive Distribution Shift as a Framework for Understanding Tractable Learning
Practical and Scalable Hamiltonian Monte Carlo Without the Metropolis Test
Balancing Fidelity and Diversity in Diffusion Models via Symmetric Attention Decomposition: Hopfield Perspective
Semi-Supervised Gaze Estimation via Disentangled Subspace Contrastive Learning
Unlearning Isn't Deletion: Investigating Reversibility of Machine Unlearning in LLMs
Epistemic Uncertainty Quantification for Pre-trained VLMs via Riemannian Flow Matching
Learning from Pairwise Preferences in Long-Term Decision Problems
Unison: Benchmarking Unified Multimodal Models via Synergistic Understanding and Generation
Principle-Evolvable Scientific Discovery via Uncertainty Minimization
Bandit Social Leaning Dynamics with Exploration Episodes
Escaping the Likelihood Trap: Geometric Diversity Optimization for Long-Form Image Captioning
WebWorld: A Large-Scale World Model for Web Agent Training
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
GEM-FI: Gated Evidential Mixtures with Fisher Modulation
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
MarketSim: Simulating Stock Markets with Large-Scale Generative Agents
LoCoT2V-Bench: Benchmarking Long-Form and Complex Text-to-Video Generation
Dimensionality Reduction with Point-distributions Similarity Invariant
Learning Unmasking Policies for Diffusion Language Models
Bridging Your Imagination with Audio-Video Generation via a Unified Director
Steering Beyond the Support: Adversarial Training on Unsupervised Jailbroken Activation Simulation
Manifold-Aligned Guided Integrated Gradients for Reliable Feature Attribution
Guideline-Grounded Evidence Accumulation for High-Stakes Agent Verification
ReVSI: Rebuilding Visual Spatial Intelligence Evaluation for Accurate Assessment of VLM 3D Reasoning
Forget-It-All: Multi-Concept Machine Unlearning via Concept-Aware Neuron Masking
Leveraging Machine Unlearning for Cost-Efficient Preference Alignment
HE-SNR: Uncovering Latent Logic via Entropy for Guiding Mid-Training on SWE-bench
Where Signals Are Sparse, We Synthesize: Reinforcing Self-Corrective Reasoning in Vision–Language Models via Rollout Augmentation
HyPER: Bridging Exploration and Exploitation for Scalable LLM Reasoning with Hypothesis Path Expansion and Reduction
Discrete Adjoint Schrödinger Bridge Sampler
MiniMax Learning of Interpretable Factored Stochastic Policies from Conjoint Data, with Uncertainty Quantification
Matrix-Free GPU Semidefinite Programming for Quantum Ordered Search at the k=6 Frontier
InertialAR: Autoregressive 3D Molecule Generation with Inertial Frames
PrivAct: Internalizing Contextual Privacy Preservation via Multi-Agent Preference Training
Train Once, Reuse Everywhere: Generalizable Implicit ICL by Routing Attention
DARC: Disagreement-Aware Alignment via Risk-Constrained Decoding
Constitutional Black-Box Monitoring for Scheming in LLM Agents
PPT-Eval: A Benchmark for Computer-Use Agents on PowerPoint Tasks
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
ATLAS: Learning to Optimally Memorize the Context at Test Time
A General Framework for Dynamic Consistent Submodular Maximization
Adaptive Multi-Round Allocation with Stochastic Arrivals
Counterfactual Occlusion-Aware Learning via Visibility Intervention for LiDAR Anomaly Detection
MoRGEN: Mixture-of-Resolutions Generative Forecasting for Irregularly Sampled Medical Time-Series Data
Mobility-Embedded POIs: Learning What A Place Is and How It Is Used from Human Movement
MeshTok: Efficient Multi-Scale Tokenization for Scalable PDE Transformers
Active Attacks: Red-teaming LLMs via Adaptive Environments
Verifiable Multimodal Reasoning: Fact-level Attribution with Multimodal Sources
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
Causal Flow Q-Learning for Robust Offline Reinforcement Learning
Is One Layer Enough? Understanding Inference Dynamics in Tabular Foundation Models
BOOSTAPR: Boosting Automated Program Repair via Execution-Grounded Reinforcement Learning with Dual Reward Models
FoeGlass: When 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
RLAnything: Forge Environment, Policy, and Reward Model in Completely Dynamic RL System
SIPO: Stabilized and Improved Preference Optimization for Aligning Diffusion Models
Parameter-Masked Decoupled Optimization for Cross-Domain Class-Incremental Learning
A Provable Expressiveness Hierarchy in Hybrid Linear-Full Attention
Non-Stationary Online Structured Prediction with Surrogate Losses
Dissect and Prune: Enhancing Robustness in AI-Generated Image Detection
Keeping a Secret Requires a Good Memory: Space Lower-Bounds for Private Algorithms
ReTabSyn: Realistic Tabular Data Synthesis via Reinforcement Learning
FIRE: Multi-fidelity Regression with Distribution-conditioned In-context Learning using Tabular Foundation Models
The cost of commitment in option-based hierarchical RL
EVMbench: Evaluating AI Agents on Smart Contract Security
Subliminal Effects in Your Data: A General Mechanism via Log-Linearity
Decouple and Cache: KV Cache Construction for Streaming Video Understanding
Identifying Partially Observed Causal Models from Heterogeneous/Nonstationary Data
MaMa: A Game-Theoretic Approach for Designing Safe Agentic Systems
Riemannian Metric Matching for Scalable Geometric Modeling of Distributions
FHAIM: Fully Homomorphic AIM for Private Synthetic Data Generation
Inference-Aware Meta-Alignment of LLMs via Non-Linear GRPO
BroRL: Scaling Reinforcement Learning via Broadened Exploration
On the Learning Dynamics of RLVR at the Edge of Competence
Latent Forcing: Reordering the Diffusion Trajectory for Pixel-Space Image Generation
OpenMAG: A Comprehensive Benchmark for Multimodal-Attributed Graph
Parameter Decorrelation via Transition-Variance Alignment for Multivariate Time-series Forecasting
Mitigating Hallucinations in Large Vision-Language Models via Causal Route Gating
Contractive Anchor Resolvent Diffusion for Incomplete Multi-View Clustering
Incentivized Exploration with Stochastic Covariates: A Two-Stage Mechanism Design for Recommender System
Mitigating Bias in Locally Constrained Decoding via Tractable Proposals
FUSE: Ensembling Verifiers with Zero Labeled Data
Shrinking the Variance: Shrinkage Baselines for Reinforcement Learning with Verifiable Rewards
Stein Diffusion Guidance: Training-Free Posterior Correction for Sampling Beyond High-Density Regions
From LLM-Generated Conjectures to Lean Formalizations: Automated Polynomial Inequality Proving via Sum-of-Squares Certificates
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
SteeringSafety: Benchmarking Representation Steering in LLMs Across Safety Perspectives
The impact of LoRA on Oversmoothing $\colon$ Understanding Catastrophic Forgetting in Mean-Field Attention Dynamics
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?
Geometric Embedding Alignment via Curvature Matching in Transfer Learning
Last-iterate Convergence of ADMM on Multi-affine Quadratic Equality Constrained Problem
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
SURGE: Surrogate Gradient Adaptation in Binary Neural Networks
Can Muon Fine-tune Adam-Pretrained Models?
GePBench: Evaluating Fundamental Geometric Perception for Multimodal Large Language Models
Ratio-Variance Regularized Policy Optimization
Separating representation from reconstruction enables scalable text encoders
XPERT: Expert Knowledge Transfer for Effective Training of Language Models
KBQA-R1: Reinforcing Large Language Models for Knowledge Base Question Answering
Identifiable Nonlinear Differentiable Causal Discovery via Independence and Adaptive Group Sparsity
Reasoning Is Not Free: Robust Adaptive Cost-Efficient Router for LLM-as-a-Judge
Flatland: The Adventures of Gradient Descent with Large Step Sizes
AIR-VLA: Vision-Language-Action Systems for Aerial Manipulation
Goal-Oriented Lower-Tail Calibration of Gaussian Processes for Bayesian Optimization
Co-Generative De Novo Functional Protein Design
An Exploration of Non-Euclidean Gradient Descent: Muon and its Many Variants
The Fisher Dimension: Instance-Dependent Complexity for Causal Discovery
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
Convex Optimization for Alignment and Preference Learning on a Single GPU
Linguistic Relative Policy Optimization for Video Anomaly Reasoning
DIVER: Diving Deeper into Distilled Data via Expressive Semantic Recovery
Efficient Online Variational Estimation via Monte Carlo Sampling
SLAT: Segment-Level Adaptive Trimming for Efficient CoT Reasoning
ShapCCS: Shapley-Driven Client Coreset Selection in Federated Learning
PGT: Procedurally Generated Tasks for improving fine-grained understanding in MLLMs
Source-Free Open-World RF Fingerprint Identification
Robust Sequential Experimental Design for A/B Testing
Item Response Scaling Laws: A Measurement Theory Approach for Efficient and Generalizable Neural Scaling Estimation
Spectral Heat Flow for Conservative Token Condensation in Vision-Language Models
Two-Stage Unit Tying for Simplifying Differentiable Logic Gate Networks
Multi-agent imitation learning with function approximation: linear Markov games and beyond
BESPOKE: Benchmark for Search-Augmented Large Language Model Personalization via Diagnostic Feedback
EvoGM: Learning to Merge LLMs via Evolutionary Generative Optimization
Toward Stable Value Alignment: Introducing Independent Modules for Consistent Value Guidance
SF-Mamba: Rethinking State Space Model for Vision
Accelerated Multiple Wasserstein Gradient Flows for Multi-objective Distributional Optimization
A Fourier perspective on the learning dynamics of neural networks: from sample complexities to mechanistic insights
Escaping the Subspace Trap: The Role of Optimizer Geometry in Model Width Expansion
Stochastic Minimum-Cost Reach-Avoid Reinforcement Learning
SecCodePRM: A Process Reward Model for Code Security
Understand and Accelerate Memory Processing Pipeline for Large Language Model Inference
Zero-Shot Rankability: Revealing Latent Ordinal Structure in Multimodal Large Language Models via Language
Multi-Round Human–AI Collaboration with User-Specified Requirements
On the Difficulty of Learning a Meta-network for Training Data Selection
R2-Router: A New Paradigm for LLM Routing with Reasoning
dTRPO : Trajectory Reduction in Policy Optimization of Diffusion Large Language Models
Three Years of r/ChatGPT: Societal Impact Evaluations from Social Media Data
Active Continual Learning with Metaplastic Binary Bayesian Neural Networks
Demystifying Multimodal Biomolecular Co-design With Intrinsic Geodesic Coupling
DualCOIL: Offline Imitation Learning from Contrasting Demonstrations
Locate then Correct: Debiasing Attention Heads in CLIP
Neural Control: Adjoint Learning Through Equilibrium Constraints
SyMerge: From Non-Interference to Synergistic Merging via Single-Layer Adaptation
ST-TGExplainer: Disentangling Stability and Transition Patterns for Temporal GNN Interpretability
The Truth Lies Somewhere in the Middle (of the Generated Tokens)
SonicMaster: Towards Controllable All-in-One Music Restoration and Mastering
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
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
Plan Then Action: High-Level Planning Guidance Reinforcement Learning for LLM Reasoning
Zero-Shot 3D Question Answering via Hierarchical View-to-Token Transportation
A Consensus Anchor-guided Hypergraph Framework For Incomplete Multi-view Clustering
D-FUSEr: Diverse Failure, Unified Success via Error-Distribution Shaping in LLM Reasoning
Monitoring LLM-based Multi-Agent Systems Against Corruptions via Node Evaluation
Greedy Coordinate Diffusion: Effective and Semantically Coherent Adversarial Attacks via Diffusion Guidance
CBV: Clean-label Backdoor Attacks on Vision Language Models via Diffusion Models
Class-Conditional Distribution Balancing for Group Robust Classification
Improved Analysis of the Accelerated Noisy Power Method with Applications to Decentralized PCA
On Local Policies for Graph-Structured Markov Decision Processes
Rashomon Sets of Falling Trees
DF-ExpEnse: Diffusion Filtered Exploration for Sample Efficient Finetuning
Video-MTR: Reinforced Multi-Turn Reasoning for Long Video Understanding
Adaptive Quasimetric Mapping : Principled Topological Abstraction for Robust Offline Goal-Conditioned Navigation
When Is Rank-1 Enough? Geometry-Guided Initialization for Parameter-Efficient Fine-Tuning
A Random Matrix Theory of Masked Self-Supervised Learning
GeoReward: Mitigating Contextual Variable Overestimation in Vision-Language Models for Cross-Market Preference Prediction
Value-as-Return: A Two-Stage Framework to Align on the Optimal Score Function
Anti-causal domain generalization: Leveraging unlabeled data
On Densest $k$-Subgraph Mining and Diagonal Loading: Optimization Landscape and Finite-Step Exact Convergence Analysis
Beyond Blind Noising: Disentangled Visual Rectification for Hallucination Mitigation in MLLMs
Adversarially Robust Control of Conditional Value-at-Risk via Kelly Conformal Inference
MODEL MERGING SCALING LAWS IN LARGE LANGUAGE MODELS
Expected Return Causes Outcome-Level Mode Collapse in Reinforcement Learning and How to Fix It with Inverse Probability Scaling
Learning from Comparison: Constrained Projection Policy Optimization for Pareto-Front Improvement
OrchJail: Jailbreaking Tool-Calling Text-to-Image Agents by Orchestration-Guided Fuzzing
SAGE: Shaping Anchors for Guided Exploration in RLVR of LLMs
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
Deep Ensemble Clustering for Visual Representation Learning
Conversation for Non-verifiable Learning: Self-Evolving Large Language Models through Meta-Evaluation
FlashOptim: Memory Efficient Optimizers for Large-Scale Training
Reason, Then Re-reason: Cross-view Revisiting Improves Spatial Reasoning
STFlow: Data-Coupled Flow Matching for Geometric Trajectory Simulation
WeatherSyn: An Instruction Tuning MLLM For Weather Forecasting Report Generation
RBCBF: Decoding Time Safety Alignment via Risk Guided Rollback and Barrier Control
FEDEMOE: IMPROVING PERSONALIZATION ON HET- EROGENEOUS FEDERATED LEARNING VIA ELASTIC MIXTURE OF EXPERTS ARCHITECTURE
Self-correcting for Debiasing Large Language Models
ImmersePro: End-to-End Stereo Video Synthesis Via Implicit Disparity Learning
Compressed Sensing for Capability Localization in Large Language Models
The Role of Target Update Frequencies in Q-Learning
Diffract: Spectral View of LLM Domain Adaptation
Procedural Pretraining: Warming Up Language Models with Abstract Data
Contrastive Geometric Learning Unlocks Unified Structure- and Ligand-Based Drug Design
FlowMAP: Flow Matching for Generalizable Agent Planning
Trust Region Inverse Reinforcement Learning
A Perturbation Approach to Unconstrained Linear Bandits
Domain Adaptation with Adaptive $f$-Divergence: Tighter Variational Representation and Generalization Bounds
Functional Adjoint Sampler: Scalable Sampling on Infinite Dimensional Spaces
Fair Decisions from Calibrated Scores: Achieving Optimal Classification While Satisfying Sufficiency
CoRe: Collaborative Reasoning via Cross Teaching
$f$-Divergence Regularized RLHF: Two Tales of Sampling and Unified Analyses
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
Normalization-equivariant Diffusion Models: Learning Posterior Samplers From Noisy And Partial Measurements
Reflex: Real-Time Vision-Language-Action Control through Streaming Inference
Mind Your Margin and Boundary: Are Your Distilled Datasets Truly Robust?
IVQ: Structured and Lightweight Vector Quantization via Binary Hierarchical Composition Inspired by $\textit{IChing}$
InteractBench: Benchmarking LLMs on Competitive Programming under Unrevealed Information
Reranker Helps, but Not Enough: Towards Strong Poisoning Attacks Against Retrieval-Augmented Generation
Unifying Deep Stochastic Processes for Image Enhancement
When Can We Trust Survival Model Evaluation ?
Per-example Gradients: a New Frontier for Understanding and Improving Optimizers
Privacy Amplification in Differentially Private Zeroth-Order Optimization with Hidden States
LLM4Branch: Large Language Model for Discovering Efficient Branching Policies of Integer Programs
Learning to Execute Graph Algorithms Exactly with Graph Neural Networks
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
Long-term Fairness with Selective Labels
Learning Treatment Representations for Downstream Instrumental Variable Regression
Dustin: Draft-Augmented Sparse Verification for Efficient Long-Context Generation with Speculative Decoding
Active Timepoint Selection for Learning Measure-Valued Trajectories
Learning-to-Optimize via Deep Unfolded Flows
CORRECT: COndensed eRror RECognition via knowledge Transfer in multi-agent systems
Clipping Bottleneck: Stabilizing RLVR via Stochastic Recovery of Near-Boundary Signals
Beyond Magnitude: Scale-Invariant Evidential Fusion for Multi-View Classification
Clustering as Reasoning: A $k$-Means Interpretation of Chain-of-Thought Graph Learning
Efficient RL Training for LLMs with Experience Replay
SI-IGCL: Subject Invariance-aware Inverse Graph Contrastive Learning for Psychiatric Disorder Identification
Task-Awareness Improves LLM Generations and Uncertainty
Learning-To-Measure: In-Context Active Feature Acquisition
Selecting Samples on Graphs: A Unified Dataset Pruning Framework for Lossless Training Acceleration
Think Fast and Slow: Step-Level Cognitive Depth Adaptation for LLM Agents
Provably Valid Uncertainty Quantification for Deep Computed Tomography
Theoretical Characterization of Generalization in Knowledge Distillation
Geodesic Flow Matching for Denoising High-Dimensional Structured Representations
Causal-aware Anomaly Detection for Tabular Data
T$^2$PO: Uncertainty-Guided Exploration Control for Stable Multi-Turn Agentic Reinforcement Learning
Foundations of Equivariant Deep Learning: Unifying Graph and Sheaf Neural Networks
AlignedNorm: Prompting Vision–Language Models via Coupled Prompt Field
SMM Transformer: Leveraging Spiking Neural Networks for Multimodal Tasks
LeakGFN: Robust Molecular Generation in Generative Flow Networks via Flow Decomposition
Evolutionary Multi-View Classification with Label Noise via Gradient and Feature Dual-Perception
DELTA4: Sparse Matrix-Vector Multiplication for Low Sparsity
HTAC: Hierarchical Task-Aware Composition for Continual Offline Reinforcement Learning
ML-Embed: Inclusive and Efficient Embeddings for a Multilingual World
Learning High-Frequency Continuous Action Chunks in Latent Space
Rethinking Multimodal Time-Series Forecasting Evaluation
Language Model Augmented Semi-Supervised Statistical Inference
Smooth Multi-Policy Causal Effect Estimation in Longitudinal Settings
EvoEGF-Mol: Evolving Exponential Geodesic Flow for Structure-based Drug Design
UniMapping: Unified SLAM Framework for Map-Centric Embodied Perception
From Noise to Control: Parameterized Diffusion Policies
From Guessing to Placeholding: A Cost-Theoretic Framework for Uncertainty-Aware Code Completion
Dissecting Causal Mechanism Shifts via FANS: Function And Noise Separation
RTPrune: Reading-Twice Inspired Token Pruning for Efficient DeepSeek-OCR Inference
Interpreting Genomic Language Models using Sparse Autoencoders
Discrete Diffusion VLA: Bringing Discrete Diffusion to Action Decoding in Vision-Language-Action Policies
InfoDLM: an Information-Adaptive Framework for Discrete Diffusion Language Model Pretraining
DisjunctiveNet: Neural Symbolic Learning via Differentiable Convexified Optimization Layers
BESplit: Bias-Compensated Split Federated Learning with Evidential Aggregation
BLISS: A Lightweight Bilevel Influence Scoring Method for Data Selection in Language Model Pretraining
Certifying Capabilities from Finite Tests: When Is It Possible?
Fast Mixing Steady-State Control in Markov Decision Processes
MEG-XL: Data-Efficient Brain-to-Text via Long-Context Pre-Training
On the Learnability of Test-Time Adaptation: A Recovery Complexity Perspective
Sharp Concentration Bounds for Vector Bundle-Valued Statistics on Manifolds
Compositional Planning with Jumpy World Models
MASH: Modeling Abstention via Selective Help-Seeking
SemRep: Code Transformation with Semantics-Preserving Representations
KernelBand: Steering LLM-based Kernel Optimization via Hardware-Aware Multi-Armed Bandits
The Latent Color Subspace: Emergent Order in High-Dimensional Chaos
Avoid What You Know: Divergent Trajectory Balance for GFlowNets
Predictive variational inference: Learn the predictively optimal posterior distribution
Do You Want to Know if Two Distributions Are Close to Each Other?Testing the Closeness With Statistical Significance
Learning Unanimously Acceptable Lotteries via Queries
When to Trust the Cheap Check: Weak and Strong Verification for Reasoning
Who’s in Charge? Disempowerment Patterns in Real-World LLM Usage
Tracing the Persona Circuit: How Large Language Models Encode and Express Character Traits
Reinforcement Learning for Non-Verifiable Problems
The Safety-Aware Denoiser for Text Diffusion Models
Text-Driven Fusion for Infrared and Visible Images: Achieving Image Scene Adaptation on Hyperbolic Space
Fantastic Reasoning Behaviors and Where to Find Them: Unsupervised Discovery of the Reasoning Process
Policy-Driven World Model Adaptation for Robust Offline Model-based Reinforcement Learning
Signature-Informed Transformer for Asset Allocation
CODiff: One-Step Diffusion Model for Camouflaged Object Detection
From Moments to Models: Graphon-Mixture Learning for Mixup and Contrastive Learning
Fast Mixture of Curvature-Aware Experts for Diverse and Dynamic Graph Topologies
PACT: Self-Evolving Physical Safety Alignment for Diffusion Policies in Embodied Manipulation
An Exponential Separation Between Quantum and Quantum-Inspired Classical Algorithms for Linear Systems
Neural–Evolutionary Symbolic Regression with Global Constraints: Constraint-Aware Decoding and Reward Shaping
Minimizing Upper Confidence Bounds: A Data-Driven Framework for Stochastic Programming
From Talking to Singing: A New Challenge for Audio-Visual Deepfake Detection
State Space Model with Continuous Limit of HiPPO Matrix: Eigenvalue Analysis and Explicit Solution Formula
Realistic Adaptive Merging
Scaling Small Agents Through Strategy Auctions
ReNF: Rethinking the Principles of Neural Long-Term Time Series Forecasters
FUSE: FK-Steered Multi-Modal Flow Matching for Efficient Simulation-Based Posterior Estimation
Scaling Laws of Global Weather Models
Learning Discriminative and Generalizable Anomaly Detector for Dynamic Graph with Limited Supervision
Privacy-Aware Data Integration for Enhanced Quantile Inference under Heterogeneity
Foundation VAE for CT Reconstruction, Augmentation, and Generation
Affine-Equivariant Kernel Space Encoding for NeRF Editing
Hyperparameter Transfer with Mixture-of-Expert Layers
AgentScore: Autoformulation of Deployable Clinical Scoring Systems
OLion: Approaching the Hadamard Ideal by Intersecting Spectral and L inf Implicit Biases
Data Agent: Learning to Select Data via End-to-End Dynamic Optimization
RefineEvo: Planning-Guided Heuristic Evolution with Bidirectional Experience
Correcting Split Selection in Online Decision Trees via Anytime-Valid Inference
Landmark-Guided Policy Optimization for Multi-Objective Language Model Selection
Why Dedicated Critics: Eliminating Target Drift in Multi-Constraint RL
Dissecting Multimodal In-Context Learning: Modality Asymmetries and Circuit Dynamics in modern Transformers
Bimodal masked language modeling for bulk RNA-seq and DNA methylation representation learning
Privacy-Aware Video Anomaly Detection: Guided Orthogonal Projection and a Comprehensive Evaluation Framework
Next-Token Prediction and Regret Minimization
One Intervention per Component is Enough: Towards Identifiability in Linear Stochastic Dynamics from Steady State
Differentiable Weightless Controllers: Learning Logic Circuits for Continuous Control
Sponge Tool Attack: Stealthy Denial-of-Efficiency against Tool-Augmented Agentic Reasoning
Transport Clustering: Solving Low-Rank Optimal Transport via Clustering
Towards One-for-All Anomaly Detection for Tabular Data
D$^3$: Dynamic Directional Graph-Constrained Data Scheduling for LLM Training
Global Geometry Is Not Enough for Vision Representations
Unifying Value Alignment and Assignment in Cross-Domain Offline Reinforcement Learning with Heterogeneous Datasets
Scalable Sampling via Generalized Fixed-Point Diffusion Matching
LakeQA: A Benchmark for Complex Exploratory QA over a Million-Scale Data Lake
FreeText: Training-Free Text Rendering via Attention Localization and Spectral Glyph Injection
SCOPE: Selective Conformal Optimized Pairwise LLM Judging
Mind the Gap: Catching Hallucinations via Evidence Drop on the Reasoning Manifold
Many Experiments, Few Repetitions, Unpaired Data, and Sparse Effects: Is Causal Inference Possible?
Benign Overfitting in Adversarial Training for Vision Transformers
Lions and Muons: Optimization via Stochastic Frank-Wolfe
DiScoFormer: Plug-In Density and Score Estimation with Transformers
WAVE: Window-Aware Vocabulary-Efficient Early-Exit for Training-Free LLM Acceleration
Deep neural networks divide and conquer dihedral multiplication
DiffuMamba: High-Throughput Diffusion LMs with Mamba Backbone
StyleDistillation: A New Insight of Image Style Enables Personalized Aesthetic Manipulation
CONTINUUM: Restoring the Contiguous Tensor Abstraction Efficiently for Dynamic AI Workloads via Hardware Virtualization
Noise as a Natural Regularizer in Markov Decision Processes: Connecting Environmental Stochasticity and Policy Simplicity
Privately Fine-Tuned LLMs Preserve Temporal Dynamics in Tabular Data
MAC-NeRF: Motion-Aware Curriculum Learning for Dynamic LiDAR NeRFs
SpecMD: A Comprehensive Study On Speculative Expert Prefetching
ReJump: A Tree-Jump Representation for Analyzing and Improving LLM Reasoning
Stochastic Lifting for Generating Trajectories of Stochastic Physical Systems
LASER: Learning Active Sensing for Continuum Field Reconstruction
TSP with predictions
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
Identifying Learnwares via Reduced Neural Conditional Mean Embedding
A Random Matrix Perspective on the Consistency of Diffusion Models
Stronger Benchmarks for Prediction as a Service with Constraints
RSF-GLLM: Bridging the Semantic Gap in Multi-Hop Knowledge Graph QA via Recurrent Soft-Flow and Decoupled LLM Generation
Tight Margin-Based Generalization Bounds for Voting Classifiers over Finite Hypothesis Sets
Co-Evolving Latent Action World Models
Neural Attention Search Linear: Towards Adaptive Token-Level Hybrid Attention Models
ReflFlow: Learning Geometry-Guided Ray Tracing for Dynamic Specular Reconstruction
Plug-and-Play Benchmarking of Reinforcement Learning Algorithms for Large-Scale Flow Control
Towards Uniformity and Alignment for Multimodal Representation Learning
Continual Learning through Control Minimization
DPO Unchained: Your Training Algorithm is Secretly Disentangled in Human Choice Theory (and Its Loss' Convexity is Dispensable)
Hierarchical Decision Making with Structured Policies: A Principled Design via Inverse Optimization
scChord: A Probabilistic Manifold Rectification Framework for RNA-to-Protein Translation
Plug-and-Play Diffusion Meets ADMM: Dual-Variable Coupling for Robust Medical Image Reconstruction
Protein Fold Classification at Scale: Benchmarking and Pretraining
Concept Heterogeneity-aware Representation Steering
The Decrypto Benchmark for Multi-Agent Reasoning and Theory of Mind
LIFT: A Novel Framework for Enhancing Long-Context Understanding of LLMs via Long Input Fine-Tuning
VSCD: Video-based Scene Change Detection in Unaligned Scenes
Unveiling the Role of Data Uncertainty in Tabular Deep Learning
Understanding MARS: When Scaling Momentum Provably Helps
A Theory of How Pretraining Shapes Inductive Bias in Fine-Tuning
A Graph Foundation Model with Cross-Modal Alignment and Modality-Aware Expert Fusion for Multi-Modal Graphs
Privasis: Synthesizing the Largest "Public" Private Dataset from Scratch
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
Flexibility-Aware Geometric Latent Diffusion for Full-Atom Peptide Design
Anchoring Self-Play for Code Repair
Disentangling Geometry, Performance, and Training in Language Models
Large Language Model Agents Are Not Always Faithful Self-Evolvers
Supervised Classification Heads as Semantic Prototypes: Unlocking Vision-Language Alignment via Weight Recycling
xLSTM Distillation: Achieving Teacher-Student Parity Through Efficient Hybrid Architectures
Equivariant Covariance Tensors: Guaranteed SPD Uncertainty for Tensor-Valued Geometric Learning
Towards the Training of Deeper Predictive Coding Neural Networks
Compositional Behavioral Semantics and Metrics for State Abstraction in Reinforcement Learning
Torus Graphs for Large Scale Neural Phase Analysis
From Internal Diagnosis to External Auditing: A VLM-Driven Paradigm for Data-Free Online Backdoor Defense
DDSVM: A Differentiable Framework for Deep Support Vector Machines with Iterative Geometry-Aware Optimization
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
Distributionally Robust Causal Abstractions
Fair Classification with Efficient and Post-hoc Controllable Fairness-Accuracy Trade-off
PowerFlow: Unlocking the Dual Nature of LLMs via Principled Distribution Matching
Dual-branch Robust Unlearnable Examples
Editable Proof Sketch for Automated Theorem Proving
Neural Vector Lyapunov–Razumikhin Certificates for Delayed Interconnected Systems
dgMARK: Decoding-Guided Watermarking for Diffusion Language Models
Neuromem: A Granular Decomposition of the Streaming Lifecycle in External Memory for LLMs
Skewness-Robust Causal Discovery in Location-Scale Noise Models
Once-for-All: Scalable Simultaneous Forecasting via Equilibrium State Estimation
CADFit: Precise Mesh-to-CAD Program Generation with Hybrid Optimization
Excited Pfaffians: Generalized Neural Wave Functions Across Structure and State
OOVDet: Low-Density Prior Learning for Zero-Shot Out-of-Vocabulary Object Detection
Fast Byte Latent Transformer
LATO: 3D Mesh Flow Matching with Structured TOpology Preserving LAtents
Test-Time Graph Search for Goal-Conditioned Reinforcement Learning
Shifting the Breaking Point of Flow Matching for Multi-Instance Editing
Softsignum: Smooth Your Signum For Better Heterogeneity Handling
Revenue Efficiency of Correlated Equilibria in First Price Auctions
FormAct: Agentic Source Editing for Rich-Format Document Generation
HiPPO Zoo: Making Implicit State Space Memory Explicit
VELR: Efficient Video Reward Feedback via Ensemble Latent Reward Models
AgentVocab: Structure-Aware Vocabulary Adaptation for Efficient LLM Agents
Revisiting OOD Generalization in Programmatic RL
LLM-Guided Communication for Cooperative Multi-Agent Reinforcement Learning
Dual Quaternion SE(3) Synchronization with Recovery Guarantees
Class-Grouped-Normalized-Momentum and Faster Hyperparameter Exploration to Tackle Class Imbalance in Federated Learning
Discriminative Attribute Graph Clustering Through Topology-Guided Contrastive Learning
Post-Training with Policy Gradients: Optimality and the Base Model Barrier
Dual-stage Contrastive Learning-enhanced Multi-view Variational Clustering
Query-Based Asymmetric Modeling with Decoupled Input–Output Rates for Speech Restoration
Beyond Correctness: Distance-Based Social Dynamics of Multi-Agent Debate
Training LLM Agents to Empower Humans
SOLAR: Self-supervised Joint Learning for Symmetric Multimodal Retrieval
Semantic Granularity Navigation in Image Editing
Stabilizing In-Context Multi-Source Domain Adaptation for Biomedical Images Through Controls
ScaleMoE: Mixture-of-Experts for Scalable Continuous Control in Actor-Critic Reinforcement Learning
Sampled hard labels from sparse targets mislead rotation invariant algorithms
A recipe for scalable attention-based ML potentials: unlocking long-range accuracy with all-to-all node attention
$\mathcal{O}(\log N)$ Latent Dimension Suffices for Universal Approximation of Permutation-invariant Function
A proximal ADMM for multiblock problems with block anti-upper triangular constraints
On the Intrinsic Limits of Transformer Image Embeddings in Non-Solvable Spatial Reasoning
Every Step Counts: Decoding Trajectories as Authorship Fingerprints of dLLMs
NeuroCLUS: A Foundation Model with Functional Clustering for Intracranial Neural Decoding
Investigating Advanced Reasoning of Large Language Models via Black-Box Interaction
Boost the Identity-Preserving Embedding for Consistent Visual Generation
Learning Context-Conditioned Predicate Semantics via Prototype Feedback
Adaptive Visual Autoregressive Acceleration via Dual-Linkage Entropy Analysis
Non-Euclidean Gradient Descent Operates at the Edge of Stability
M-IDoL: Information Decomposition for Modality-Specific and Diverse Representation Learning in Medical Foundation Model
Attn-QAT: 4-Bit Attention With Quantization-Aware Training
Memory-Efficient LLM Pretraining via Minimalist Optimizer Design
LLM Priors for ERM over Programs
LLM4Cov: Execution-Grounded Agent Learning for High-Coverage Hardware Verification
Self-Distillation Enables Continual Learning
Distribution-Calibrated Inference Time Compute for Thinking LLM-as-a-Judge
Embodied Task Planning via Graph-Informed Action Generation with Large Lanaguage Model
LatentLens: Revealing Highly Interpretable Visual Tokens in LLMs
Instance-Level Costs for Nuanced Classifier Evaluation
Optimal Rates for Feasible Payoff Set Estimation in Games
When less gives more: bias from small dataset can speed up training
Collaborative Learning for Semi-Supervised LiDAR Semantic Segmentation
Lost in Context: Discovering Context Anxiety in 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
Diversity-Aware Recursive Feature Multiple Kernel Learning
ConFlux: Multivariate Time Series in Flux, One Unified Forecast in Confluence
EpiCoCo: De Novo Epitope Generation via MHC-Context Co-Modeling and Contrastive Affinity Guidance
Practical and Optimal Algorithm for Linear Contextual Bandits with Rare Parameter Updates
IsoCompute Playbook: Optimally Scaling Sampling Compute for LLM RL
Fast Reconstruction of Mixtures of Bernoulli Product Distributions
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
Robust In-Context Reinforcement Learning Under Reward Poisoning Attacks
VIA-SD: Verification via Intra-Model Routing for Speculative Decoding
ExpAlign: Expectation-Guided Vision–Language Alignment for Open-Vocabulary Grounding
MotionGRPO: Overcoming Low Intra-Group Diversity in GRPO-Based Egocentric Motion Recovery
Optimal Self-Consistency for Efficient Reasoning with Large Language Models
Learn from Your Mistakes: Tree-like Self-Play on Vulnerability Nodes 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
ProactiveLLM: Learning Active Interaction for Streaming Large Language Models
Human-in-the-Loop Policy Optimization for Preference-Based Multi-Objective Reinforcement Learning
Latent Collaboration in Multi-Agent Systems
Fast KV Compaction via Attention Matching
Improving the Performance and Learning Stability of Parallelizable RNNs Designed for Ultra-Low Power Applications
PCA of Probability Measures: Sparse and Dense Sampling Regimes
Universal Algorithm-Implicit Learning
3D Scene Assertion Verification
Efficient Inference for Noisy LLM-as-a-Judge Evaluation
Principled RL for Flow Matching Emerges From the Chunk-level Policy Optimization
Toward Structural Multimodal Representations: Specialization, Selection, and Sparsification via Mixture-of-Experts
JADAI: Jointly Amortizing Adaptive Design and Bayesian Inference
Blocking the Leakage: Manifold-Aware Gradient Projection for Long-Horizon Test-Time Adaptation
Diversity Over Frequency: Rethinking Tool Use in Visual Chain-of-Thought Agents
Thinned Mean Field Langevin Dynamics
Multi-Objective Bayesian Optimization via Adaptive $\varepsilon$-Constraint Decomposition
Interpretability and Generalization Bounds for Learning Spatial Physics
Faster Activation Functions at the Edge for Post-Training Speedups
BEST: Benchmarking Efficiency in Space and Time for LLM-Generated Code
From Backward Spreading to Forward Replay: Revisiting Target Construction in LLM Parameter Editing
Flexible Kernels for Protein Property Prediction
Performative Learning Theory
TimeOmni-VL: Unified Models for Time Series Understanding and Generation
$\textit{S}$-SPPO: Semantic-Calibrated Self-Play Preference Optimization
Spectra: Rethinking Optimizers for LLMs Under Spectral Anisotropy
Chain-of-Thought Gradient Descent
Expanding the Chaos: Neural Operator for Stochastic (Partial) Differential Equations
Interaction-Breaking Adversarial Learning Framework for Robust Multi-Agent Reinforcement Learning
DiasR: Dual-Modal Identity-Anchored Sparse Routing for Efficient Multi-Subject Video Generation
Self-Augmenting Retrieval for Diffusion Language Models
MMClima: A Framework for Multimodal Climate Science Data and Evaluation
From geometry to dynamics: Learning overdamped Langevin dynamics from sparse observations with geometric constraints
Hallucination is a Consequence of Space-Optimality: A Rate-Distortion Theorem for Membership Testing
Optimal structure learning and conditional independence testing
Spectral Gradient Descent Mitigates Anisotropy-Driven Misalignment: A Case Study in Phase Retrieval
Evidential Copula Concept Embedding Models
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
Security–Fidelity Tradeoffs: No Universal Defense Against Prompt Injection
Evaluating AI Grading on Real-World Handwritten College Mathematics: A Large-Scale Study Toward a Benchmark
Grounding Multi-Hop Reasoning in Structural Causal Models via Group Relative Policy Optimization
The Devil is in the Condition Numbers: Why is GLU Better than non-GLU Structure?
FiGuRO - Intrinsic Dimension Estimation for Multi-Modal Data
Dynamics and representation structure of local approximations to gradient-based learning in linear recurrent neural networks
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
Segment-driven Structural Induction and Semantic Alignment for Heterogeneous Tabular Representation
Tightening the Score Matching Gap for Diffusion Models
FRIGID: Scaling Diffusion-Based Molecular Generation from Mass Spectra at Training and Inference Time
Who Gets Credit or Blame? Attributing Accountability in Modern AI Systems
CoFrGeNet: Continued Fraction Architectures for Language Generation
Impact of Connectivity on Laplacian Representations in Reinforcement Learning
ProjQ: Project-and-Quantize for Adapter-Aware LLM Compression
Learning to Theorize the World from Observation
MODEL SOUPS NEED ONLY ONE INGREDIENT
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
Safe and Scalable Web Agent Learning via Recreated Websites
PSMix: Robust Point Cloud Recognition through Spectral Domain Mixing
RL-SPH: Learning to Achieve Feasible Solutions for Integer Linear Programs
Does Your Reasoning Model Implicitly Know When to Stop Thinking?
Normalized Rewards for Preference Optimization
Gradient Smoothing: Coupling Layer-wise Updates for Improved Optimization
Federated Manifold Learning (FML): Tackling Domain Heterogeneity with Structural Knowledge Transfer
MulFCoder: Framework-conditioned Multi-agent for MLLM-based Multi-framework Front-end Code Generation
ElicitR: Unlocking Latent Reasoning in Dense Retrievers via Generative Regularization
SCOUT: Cyclic Causal Discovery Under Soft Interventions with Unknown Targets
Open Materials Generation with Inference-Time Reinforcement Learning
Deep Incentive Design with Differentiable Equilibrium Blocks
Learning, Solving and Optimizing PDEs with TensorGalerkin: an efficient high-performance Galerkin assembly algorithm
PerturbDiff: Functional Diffusion for Single-Cell Perturbation Modeling
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
N2M: Bridging Navigation and Manipulation by Learning Pose Preference from Rollout
On Regret Bounds of Thompson Sampling for Bayesian Optimization
AGoQ: Activation and Gradient Quantization for Memory-Efficient Distributed Training of LLMs
Chunk-Guided Q-Learning
Di-BiLPS: Denoising induced Bidirectional Latent-PDE-Solver under Sparse Observations
Failure is Feedback: History-Aware Backtracking for Agentic Traversal in Multimodal Graphs
InfiMed-ORBIT: Aligning LLMs on Open-Ended Complex Tasks via Rubric-Based Incremental Training
Do We Need Adam? Surprisingly Strong and Sparse Reinforcement Learning with SGD in LLMs
Textual Supervision Enhances Geospatial Representations in Vision-Language Models
No Free Lunch: Non-Asymptotic Analysis of Prediction-Powered Inference
How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs
RaBitQCache: Rotated Binary Quantization for KVCache in Long Context LLM Inference
Why Specialist Models Still Matter: A Heterogeneous Multi-Agent Paradigm for Medical Artificial Intelligence
Attention's forward pass and Frank-Wolfe
HiST: A Hierarchical Sparse Transformer for Cross-Modal Spatial Transcriptomics Modeling
CompleteP for RL: Maintaining Feature Learning When Scaling Deep Reinforcement Learning
FlashSketch: Sketch-Kernel Co-Design for Fast Sparse Sketching on GPUs
When Embedding-Based Defenses Fail: Rethinking Safety in LLM-Based Multi-Agent Systems
Scaling Law for Quantization-Aware Training
LLMs as Noisy Channels: A Shannon Perspective on Model Capacity and Scaling Laws
Spectral Collapse Drives Loss of Plasticity in Deep Continual Learning
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