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Workshop

2nd Workshop on Models of Human Feedback for AI Alignment (MoFA)

Belen Martin Urcelay ⋅ Micah Carroll ⋅ Maria Teresa Parreira ⋅ Thomas Kleine Buening ⋅ Andreas Krause ⋅ Anca Dragan
Project Page [ OpenReview] 

Abstract

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Schedule

Timezone: Asia/Seoul
1:00 AM
Opening Remarks
1:40 AM
Aligned Textual Scoring Rule
Yuxuan Lu ⋅ Yifan Wu ⋅ Jason Hartline ⋅ Michael Curry
1:55 AM
Copilot Arena: A Platform for Code LLM Evaluation in the Wild
Wayne Chi ⋅ Valerie Chen ⋅ Anastasios Angelopoulos ⋅ Wei-Lin Chiang ⋅ Aditya Mittal ⋅ Naman Jain ⋅ Tianjun Zhang ⋅ Ion Stoica ⋅ Chris Donahue ⋅ Ameet Talwalkar
2:10 AM
Few-shot Steerable Alignment: Adapting Rewards and LLM Policies with Neural Processes
Katarzyna Kobalczyk ⋅ Claudio Fanconi ⋅ Hao Sun ⋅ Mihaela van der Schaar
3:00 AM
Cultivating Pluralism In Algorithmic Monoculture: The Community Alignment Dataset
Lily Zhang ⋅ Smitha Milli ⋅ Karen Jusko ⋅ Jonathan Smith ⋅ Brandon Amos ⋅ Wassim Bouaziz ⋅ Jack Kussman ⋅ Manon Revel ⋅ Lisa Titus ⋅ Bhaktipriya Radharapu ⋅ Jane Dwivedi-Yu ⋅ Vidya Sarma ⋅ Kristopher Rose ⋅ Maximilian Nickel
3:15 AM
Deep Context-Dependent Choice Model
Shuhan Zhang ⋅ Zhi Wang ⋅ Rui Gao ⋅ Shuang Li
6:05 AM
Panel
Stephen Casper ⋅ Yilun Zhou ⋅ Goran Radanovic ⋅ Natasha Jaques
7:00 AM
Coffee Break
7:30 AM
Doctor Approved: Generating Medically Accurate Skin Disease Images through AI–Expert Feedback
Janet Wang ⋅ Yunbei Zhang ⋅ Zhengming Ding ⋅ Jihun Hamm
7:45 AM
Dropping Just a Handful of Preferences Can Change Top Large Language Model Rankings
Jenny Huang ⋅ Yunyi Shen ⋅ Dennis Wei ⋅ Tamara Broderick
8:55 AM
Closing Remarks
→ Improvement-Guided Iterative DPO for Diffusion Models
Ying Fan ⋅ Fei Deng ⋅ Yang Zhao ⋅ Sahil Singla ⋅ Rahul Jain ⋅ Tingbo Hou ⋅ Kangwook Lee ⋅ Feng Yang ⋅ Deepak Ramachandran ⋅ Qifei Wang
→ Inference-Time Reward Hacking in Large Language Models
Hadi Khalaf ⋅ Claudio Mayrink Verdun ⋅ Alex Oesterling ⋅ Himabindu Lakkaraju ⋅ Flavio Calmon
→ FSPO: Few-Shot Preference Optimization of Synthetic Preference Data Elicits LLM Personalization to Real Users
Anikait Singh ⋅ Sheryl Hsu ⋅ Kyle Hsu ⋅ Eric Mitchell ⋅ Stefano Ermon ⋅ Tatsunori Hashimoto ⋅ Archit Sharma ⋅ Chelsea Finn
→ Enhancing Personalized Multi-Turn Dialogue with Curiosity Reward
Yanming Wan ⋅ Jiaxing Wu ⋅ Marwa Abdulhai ⋅ Lior Shani ⋅ Natasha Jaques
→ Tracing Human-like Traits in LLMs: Origins, Real-World Manifestation, and Controllability
Pengrui Han ⋅ Rafal Kocielnik ⋅ Peiyang Song ⋅ Ramit Debnath ⋅ Dean Mobbs ⋅ Anima Anandkumar ⋅ R. Michael Alvarez
→ ReDit: Reward Dithering for Improved LLM Policy Optimization
Chenxing Wei ⋅ Jiarui Yu ⋅ Ying He ⋅ Hande Dong ⋅ Yao Shu ⋅ Fei Yu
→ Mitigating Fine-tuning Risks in LLMs via Safety-Aware Probing Optimization
Chengcan Wu ⋅ Zhixin Zhang ⋅ Zeming Wei ⋅ Yihao Zhang ⋅ Meng Sun
→ Playing the Data: Video Games as a Tool to Annotate and Train Models on Large Datasets
Parham Ghasemloo Gheidari ⋅ Kai-Hsiang Chang ⋅ Roman Sarrazin-Gendron ⋅ Renata Mutalova ⋅ Alexander Butyaev ⋅ Attila Szantner ⋅ Jérôme Waldispühl
→ In-Context Personalized Alignment with Feedback History under Counterfactual Evaluation
Xisen Jin ⋅ Zheng Li ⋅ Zhenwei DAI ⋅ Hui Liu ⋅ Xianfeng Tang ⋅ Chen Luo ⋅ Rahul Goutam ⋅ Xiang Ren ⋅ Qi He
→ Towards a Sharp Analysis of Offline Policy Learning for $f$-Divergence-Regularized Contextual Bandits
Qingyue Zhao ⋅ Kaixuan Ji ⋅ Heyang Zhao ⋅ Tong Zhang ⋅ Quanquan Gu
→ Multi-Task Reward Learning from Human Ratings
Mingkang Wu ⋅ Devin White ⋅ Evelyn Rose ⋅ Vernon Lawhern ⋅ Nicholas Waytowich ⋅ Yongcan Cao
→ Doubly Robust Alignment for Large Language Models
Erhan Xu ⋅ Kai Ye ⋅ Hongyi Zhou ⋅ Luhan Zhu ⋅ Francesco Quinzan ⋅ Chengchun Shi
→ KL-Regularised Q-Learning: A Token-level Action-Value perspective on Online RLHF
Lennie Wells ⋅ Edward J. Young ⋅ Jason Brown ⋅ Sergio Bacallado
→ Entropy Controllable Direct Preference Optimization
Motoki Omura ⋅ Yasuhiro Fujita ⋅ Toshiki Kataoka
→ Understanding Likelihood Over-optimisation in Direct Alignment Algorithms
Zhengyan Shi ⋅ Sander Land ⋅ Acyr Locatelli ⋅ Matthieu Geist ⋅ Max Bartolo
→ Advancing LLM Safe Alignment with Safety Representation Ranking
Tianqi Du ⋅ Zeming Wei ⋅ Quan Chen ⋅ Chenheng Zhang ⋅ Yisen Wang
→ LoRe: Personalizing LLMs via Low-Rank Reward Modeling
Avinandan Bose ⋅ Zhihan Xiong ⋅ Yuejie Chi ⋅ Simon Du ⋅ Lin Xiao ⋅ Maryam Fazel
→ Online Learning and Equilibrium Computation with Ranking Feedback
Mingyang Liu ⋅ Yongshan Chen ⋅ Zhiyuan Fan ⋅ Gabriele Farina ⋅ Asuman Ozdaglar ⋅ Kaiqing Zhang
→ Efficient Generative Models Personalization via Optimal Experimental Design
Guy Schacht ⋅ Mojmir Mutny ⋅ Riccardo De Santi ⋅ Ziyad Sheebaelhamd ⋅ Andreas Krause
→ Aligning Neural Style Representations for Style-based Clustering
Abhishek Dangeti ⋅ Pavan Gajula ⋅ Vikram Jamwal ⋅ Vivek Srivastava
→ Aggregated Individual Reporting for Post-Deployment Evaluation
Jessica Dai ⋅ Inioluwa Raji ⋅ Benjamin Recht ⋅ Irene Y. Chen
→ Full-Stack Alignment: Co-Aligning AI and Institutions with Thicker Models of Value
Ryan Lowe ⋅ Joe Edelman ⋅ Tan Zhi-Xuan ⋅ Oliver Klingefjord ⋅ Ellie Hain ⋅ Vincent Wang-Maścianica ⋅ Atrisha Sarkar ⋅ Michiel Bakker ⋅ Fazl Barez ⋅ Matija Franklin ⋅ Andreas Haupt ⋅ Jobstq Heitzig ⋅ Wesley H. Holliday ⋅ Julian Jara-Ettinger ⋅ Atoosa Kasirzadeh ⋅ Ryan Kearns ⋅ James Kirkpatrick ⋅ Andrew Koh ⋅ Joel Lehman ⋅ Sydney Levine ⋅ Manon Revel ⋅ Ivan Vendrov
→ Selective Preference Aggregation
Shreyas Kadekodi ⋅ Hayden McTavish ⋅ Berk Ustun
→ Auto-Guideline Alignment: Probing and Simulating Human Ideological Preferences in LLMs via Prompt Engineering
Chien-Hua Chen ⋅ Chang Chih Meng ⋅ Li-Ni Fu ⋅ Hen-Hsen Huang ⋅ I-Chen Wu
→ EconEvals: Benchmarks and Litmus Tests for LLM Agents in Unknown Environments
Sara Fish ⋅ Julia Shephard ⋅ Minkai Li ⋅ Ran Shorrer ⋅ Yannai A. Gonczarowski
→ Alignment as Distribution Learning: Your Preference Model is Explicitly a Language Model
Jihun Yun ⋅ Juno Kim ⋅ Jongho Park ⋅ Junhyuck Kim ⋅ Jongha (Jon) Ryu ⋅ Jaewoong Cho ⋅ Kwang-Sung Jun
→ Rewrite-to-Rank: Optimizing Ad Visibility via Retrieval-Aware Text Rewriting
Chloe Ho ⋅ Ishneet Singh ⋅ Diya Sharma ⋅ Tanvi Anumandla ⋅ Michael Lu ⋅ Vasu Sharma ⋅ Kevin Zhu
→ Robust Multi-Objective Controlled Decoding of Large Language Models
Seongho Son ⋅ William Bankes ⋅ Sangwoong Yoon ⋅ Shyam Sundhar Ramesh ⋅ Xiaohang Tang ⋅ Ilija Bogunovic
→ CulturalFrames: Assessing Cultural Expectation Alignment in Text-to-Image Models and Evaluation Metrics
Perampalli Shravan Nayak ⋅ Mehar Bhatia ⋅ Xiaofeng Zhang ⋅ Verena Rieser ⋅ Lisa Hendricks ⋅ Sjoerd van Steenkiste ⋅ Yash Goyal ⋅ Karolina Stanczak ⋅ Aishwarya Agrawal
→ In-Context Alignment at Scale: When More is Less
Neelabh Madan ⋅ Lakshmi Subramanian
→ Dynamic Guardian Models: Realtime Content Moderation With User-Defined Policies
Monte Hoover ⋅ Vatsal Baherwani ⋅ Neel Jain ⋅ Khalid Saifullah ⋅ Joseph Vincent ⋅ Chirag Jain ⋅ Melissa Rad ⋅ C. Bayan Bruss ⋅ Ashwinee Panda ⋅ Tom Goldstein
→ On the strength of goodhart's law
Adrien Majka ⋅ Wassim Bouaziz ⋅ El-Mahdi El-Mhamdi
→ Reasoning Isn't Enough: Examining Truth-Bias and Sycophancy in LLMs
Emilio Barkett ⋅ Olivia Long ⋅ Madhavendra Thakur
→ A Unified Perspective on Reward Distillation Through Ratio Matching
Kenan Hasanaliyev ⋅ Schwinn Saereesitthipitak ⋅ Rohan Sanda
→ Geometry-Aware Preference Learning for 3D Texture Generation
AmirHossein Zamani ⋅ Tianhao Xie ⋅ Amir Aghdam ⋅ Tiberiu Popa ⋅ Eugene Belilovsky
→ What Matters when Modeling Human Behavior using Imitation Learning?
Aneri Muni ⋅ Esther Derman ⋅ Vincent Taboga ⋅ Pierre-Luc Bacon ⋅ Erick Delage
→ Expected Reward Prediction, with Applications to Model Routing
Kenan Hasanaliyev ⋅ Silas Alberti ⋅ Jenny Hamer ⋅ Dheeraj Rajagopal ⋅ Kevin Robinson ⋅ Jasper Snoek ⋅ Victor Veitch ⋅ Alexander D'Amour
→ Language Model Personalization via Reward Factorization
Idan Shenfeld ⋅ Felix Faltings ⋅ Pulkit Agrawal ⋅ Aldo Pacchiano
→ Robust Reinforcement Learning from Human Feedback for Large Language Models Fine-Tuning
Kai Ye ⋅ Hongyi Zhou ⋅ Jin Zhu ⋅ Francesco Quinzan ⋅ Chengchun Shi
→ Theoretical Analysis of KL-regularized RLHF with Multiple Reference Models
Gholamali Aminian ⋅ Amir R. Asadi ⋅ Idan Shenfeld ⋅ Youssef Mroueh
→ Alignment of Large Language Models with Constrained Learning
Botong Zhang ⋅ Shuo Li ⋅ Ignacio Hounie ⋅ Osbert Bastani ⋅ Dongsheng Ding ⋅ Alejandro Ribeiro
→ Robust Reward Modeling via Causal Rubrics
Pragya Srivastava ⋅ Harman Singh ⋅ Rahul Madhavan ⋅ Gandharv Patil ⋅ Sravanti Addepalli ⋅ Arun Sai Suggala ⋅ Rengarajan Aravamudhan ⋅ Soumya Sharma ⋅ Anirban Laha ⋅ Aravindan Raghuveer ⋅ Karthikeyan Shanmugam ⋅ Doina Precup
→ ActiveDPO: Active Direct Preference Optimization for Sample-Efficient Alignment
Xiaoqiang Lin ⋅ Arun Verma ⋅ Zhongxiang Dai ⋅ Daniela Rus ⋅ See-Kiong Ng ⋅ Bryan Kian Hsiang Low
→ Mechanism Design for Alignment via Human Feedback
Julian Manyika ⋅ Michael Wooldridge ⋅ Jiarui Gan
→ Composition and Alignment of Diffusion Models using Constrained Learning
Shervin Khalafi ⋅ Ignacio Hounie ⋅ Dongsheng Ding ⋅ Alejandro Ribeiro