Reward Modeling

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24 papers in the last four weeks, up 118% on the four weeks before. 0.2% of all new papers.

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Efficiently Aligning Language Models with Online Natural Language Feedback
May 5, 2026Christine Ye, Joe BentonReward Modeling RL for Language Models
Stanford University · Anthropic Fellows Program for Safety Research · Anthropic
FINER-SQL: Boosting Small Language Models for Text-to-SQL
May 5, 2026Thanh Dat Hoang, Thanh Trung Huynh, Matthias Weidlich +4Reward Modeling Small Language Models
Griffith University (Australia) · VinUniversity (Vietnam) · Humboldt-Universitat zu Berlin (Germany) +1
Replacing Parameters with Preferences: Federated Alignment of Heterogeneous Vision-Language Models
May 5, 2026Shule Lu, Yujing Wang, Hainan Zhang +5Reward Modeling Preference Optimization
Beijing Advanced Innovation Center for Future Blockchain and Privacy Computing · Institute of Artificial Intelligence, Beihang University, China · MAIS, Institute of Automation, Chinese Academy of Sciences, China +2
RMGAP: Benchmarking the Generalization of Reward Models across Diverse Preferences
May 3, 2026Yangyang Zhou, Yi-Chen LiReward Modeling LLM Evaluation
Beijing University of Posts and Telecommunications · National Key Laboratory for Novel Software Technology, Nanjing University, China · School of Artificial Intelligence, Nanjing University, China
Adaptive Pluralistic Alignment: A pipeline for dynamic artificial democracy
May 2, 2026Rachel FreedmanReward Modeling LLM Alignment
Department of Electrical Engineering and Computer Science, University of California, Berkeley, USA.
Themis: Training Robust Multilingual Code Reward Models for Flexible Multi-Criteria Scoring
May 1, 2026Indraneil Paul, Goran Glavaš, Iryna GurevychReward Modeling Reward Model Evaluation
UKP Lab, TU Darmstadt and National Research Center for Applied Cybersecurity ATHENE · Center for Artificial Intelligence and Data Science, University of Würzburg
PrefMoE: Robust Preference Modeling with Mixture-of-Experts Reward Learning
May 1, 2026Ziqin Yuan, Ruiqi Wang, Dezhong Zhao +2Reward Modeling Mixture of Experts
1Purdue University, West Lafayette, IN, USA. · 2Beijing University of Chemical Technology, Beijing, China. · 3Indiana University Bloomington, Bloomington, IN, USA.
AesRM: Improving Video Aesthetics with Expert-Level Feedback
Apr 30, 2026Yujin Han, Yujie Wei, Yefei He +7Reward Modeling Video Quality Assessment
The University of Hong Kong · Alibaba Group · Fudan University +3
Leveraging Verifier-Based Reinforcement Learning in Image Editing
Apr 30, 2026Hanzhong Guo, Jie Wu, Jie Liu +6Reward Modeling Reinforcement Learning
School of Computing and Data Science, The University of Hong Kong · ByteDance Seed · CUHK +1
Debiasing Reward Models via Causally Motivated Inference-Time Intervention
Apr 30, 2026Kazutoshi Shinoda, Kosuke Nishida, Kyosuke NishidaReward Modeling LLM Alignment
Human Informatics Labs., NTT, Inc.
From Coarse to Fine: Benchmarking and Reward Modeling for Writing-Centric Generation Tasks
Apr 30, 2026Qingyu Ren, Tianjun Pan, Xingzhou Chen +1Reward Modeling RL for Language Models
Shanghai Key Laboratory of Data Science, College of Computer Science and Artificial Intelligence, Fudan University · 2Shanghai Artificial Intelligence Laboratory
reward-lens: A Mechanistic Interpretability Library for Reward Models
Apr 28, 2026Mohammed Suhail B NadafReward Modeling LLM Interpretability
When Errors Can Be Beneficial: A Categorization of Imperfect Rewards for Policy Gradient
Apr 28, 2026Shuning Shang, Hubert Strauss, Stanley Wei +2Reward Modeling Policy Gradient
Princeton Language and Intelligence, Princeton University
Model-Free Inference of Investor Preferences: A Relative Entropy IRL Approach
Apr 27, 2026Chen XuReward Modeling Reinforcement Learning
Department of Engineering, Shenzhen MSU-BIT University. Address: 1 International University Park Road, Longgang District, Shenzhen, Guangdong, China.
Explanation Quality Assessment as Ranking with Listwise Rewards
Apr 27, 2026Thomas Bailleux, Tanmoy Mukherjee, Emmanuel Lonca +2Reward Modeling Learning to Rank
CRIL, Univ. Artois & CNRS, France · Institut Universitaire de France
Reward Models Are Secretly Value Functions: Temporally Coherent Reward Modeling
Apr 24, 2026Alex NikulkovReward Modeling Value Function Estimation
AI at Meta
ARES: Adaptive Red-Teaming and End-to-End Repair of Policy-Reward System
Apr 20, 2026Jiacheng Liang, Yao Ma, Tharindu Kumarage +5Reward Modeling Adversarial Attacks on LLMs
Stony Brook University · Amazon Nova Responsible AI
PARM: Pipeline-Adapted Reward Model
Apr 20, 2026Xingyu Fan, Wei Shao, Jiacheng Liu +2Reward Modeling LLM-Based Program Synthesis
QuantumQA: Enhancing Scientific Reasoning via Physics-Consistent Dataset and Verification-Aware Reinforcement Learning
Apr 20, 2026Songxin Qu, Tai-Ping Sun, Yun-Jie Wang +8Reward Modeling Scientific QA
Institute of Advanced Technology, University of Science and Technology of China · Institute of Artificial Intelligence, Hefei Comprehensive National Science Center · School of Physics, University of Science and Technology of China +2
TinyJudge: Unverifiable Constraint Alignment via Lightweight Specialist Ensembles
Apr 19, 2026Yirong Zeng, Yufei Liu, Xiao Ding +9Reward Modeling LLM Alignment
Harbin Institute of Technology SCIR Lab · Peking University · Huawei Technologies Co., Ltd
AgentV-RL: Scaling Reward Modeling with Agentic Verifier
Apr 17, 2026Jiazheng Zhang, Ziche Fu, Zhiheng Xi +13Reward Modeling RL for Language Model Reasoning
College of Computer Science and Artificial Intelligence, Fudan University · Huazhong University of Science and Technology · The University of Hong Kong +3
Relational Preference Encoding in Looped Transformer Internal States
Apr 10, 2026Jan KirinPairwise Preference Learning Reward Modeling
Unbiased Reward Modeling from Implicit Feedback for LLM Alignment
Mar 24, 2026Hao Wang, Haocheng Yang, Licheng Pan +7Reward Modeling LLM Alignment
Peking University · Xiaohongshu Inc. · National University of Singapore +1
When Rubrics Fail: Error Enumeration as Reward in Reference-Free RL Post-Training for Virtual Try-On
Mar 5, 2026Wisdom Ikezogwo, Mehmet Saygin Seyfioglu, Ranjay Krishna +1Reward Modeling Reference-Free Evaluation
University of Washington, Seattle, USA · Amazon, Seattle, USA · Allen Institute for AI
MARS: Margin and Semantic-Aware Data Augmentation for Reward Modeling
Feb 19, 2026Payel Bhattacharjee, Osvaldo Simeone, Ravi TandonReward Modeling Synthetic Data Augmentation
University of Arizona · Tucson, AZ, USA · Northeastern University London +1
GRRM: Group Relative Reward Modeling for Machine Translation
Feb 15, 2026Sen Yang, Shanbo Cheng, Lu Xu +2Reward Modeling RL for Language Models
National Key Laboratory for Novel Software Technology, Nanjing University · Singapore University of Technology and Design
Small Reward Models via Backward Inference
Feb 14, 2026Yike Wang, Faeze Brahman, Shangbin Feng +3Reward Modeling RL for Language Models
University of Washington · Allen Institute for Artificial Intelligence
Reward Modeling for Reinforcement Learning-Based LLM Reasoning: Design, Challenges, and Evaluation
Feb 10, 2026Pei-Chi Pan, Yingbin Liang, Sen LinReward Modeling Reward Hacking
Department of Computer Science University of Houston · The Ohio State University · University of Houston
Joint Reward Modeling: Internalizing Chain-of-Thought for Efficient Visual Reward Models
Feb 7, 2026Yankai Yang, Yancheng Long, Hongyang Wei +12Reward Modeling Multimodal Reward Modeling
Harbin Institute of Technology, Shenzhen. · Kuaishou Technology.
CodeScaler: Scaling Code LLM Training and Test-Time Inference via Reward Models
Feb 4, 2026Xiao Zhu, Xinyu Zhou, Boyu Zhu +5RL for Code Generation Reward Modeling
LARK, HKUST(GZ) · Kuaishou Technology · UCL +3

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Efficiently Aligning Language Models with Online Natural Language Feedback

Christine Ye, Joe Benton

Stanford University · Anthropic Fellows Program for Safety Research · Anthropic

Reward Modeling RL for Language Models LLM Alignment

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Reinforcement learning with verifiable rewards has been used to elicit impressive performance from language models in many domains. But, broadly beneficial deployments of AI may require us to train models with strong capabilities in "fuzzy", hard-to-supervise domains. In this paper, we develop methods to align language models in fuzzy domains where human experts are still able to provide high-quality supervision signal, but only for a small number of model outputs, using online natural language feedback. Specifically, we train models by iteratively optimizing against proxy reward signals, stopping at the point of over-optimization, collecting fresh expert supervision, and updating the proxy reward. We construct proxy reward models from language models using in-context learning (ICL) and fine-tuning. We test our methods by eliciting creative writing and alignment research capabilities in Qwen3-8B and Haiku 4.5 respectively. For Qwen3-8B, ICL methods recover up to 35% of performance with 50x fewer expert samples, while fine-tuning methods recover 80% with up to 20x fewer samples and 100% with 3x fewer samples. For Haiku 4.5, ICL methods recover up to 35% of performance with 30x fewer samples, and fine-tuning methods recover 100% with 10x fewer samples. Our results suggest that online natural language feedback can substantially improve the data efficiency of expert supervision.

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