Papers
What Are Step-Level Reward Models Rewarding? Counterintuitive Findings from MCTS-Boosted Mathematical Reasoning
Yiran Ma, Zui Chen, Tianqiao Liu et al.
M-RewardBench: Evaluating Reward Models in Multilingual Settings
Srishti Gureja, Lester James Validad Miranda, Shayekh Bin Islam et al.
RAG-RewardBench: Benchmarking Reward Models in Retrieval Augmented Generation for Preference Alignment
Zhuoran Jin, Hongbang Yuan, Tianyi Men et al.
RewardBench: Evaluating Reward Models for Language Modeling
Nathan Lambert, Valentina Pyatkin, Jacob Morrison et al.
AMoPO: Adaptive Multi-objective Preference Optimization without Reward Models and Reference Models
Qi Liu, Jingqing Ruan, Hao Li et al.
Error Typing for Smarter Rewards: Improving Process Reward Models with Error-Aware Hierarchical Supervision
Tej Deep Pala, Panshul Sharma, Amir Zadeh et al.
RM-Bench: Benchmarking Reward Models of Language Models with Subtlety and Style
Yantao Liu, Zijun Yao, Rui Min et al.
Ensembling Large Language Models with Process Reward-Guided Tree Search for Better Complex Reasoning
Sungjin Park, Xiao Liu, Yeyun Gong et al.
Not All Voices Are Rewarded Equally: Probing and Repairing Reward Models across Human Diversity
Zihao Li, Feihao Fang, Xitong Zhang et al.
Reward-Directed Score-Based Diffusion Models via q-Learning
Xuefeng Gao, Jiale Zha, Xun Yu Zhou
VL-RewardBench: A Challenging Benchmark for Vision-Language Generative Reward Models
Lei Li, Yuancheng Wei, Zhihui Xie et al.
RewardDS: Privacy-Preserving Fine-Tuning for Large Language Models via Reward Driven Data Synthesis
Jianwei Wang, Chengming Shi, Junyao Yang et al.
Reward Fine-Tuning Two-Step Diffusion Models via Learning Differentiable Latent-Space Surrogate Reward
Zhiwei Jia, Yuesong Nan, Huixi Zhao et al.
SynthesizeMe! Inducing Persona-Guided Prompts for Personalized Reward Models in LLMs
Michael J. Ryan, Omar Shaikh, Aditri Bhagirath et al.
Cheems: A Practical Guidance for Building and Evaluating Chinese Reward Models from Scratch
Xueru Wen, Jie Lou, Zichao Li et al.
Mutual-Taught for Co-adapting Policy and Reward Models
Tianyuan Shi, Canbin Huang, Fanqi Wan et al.
PRMBench: A Fine-grained and Challenging Benchmark for Process-Level Reward Models
Mingyang Song, Zhaochen Su, Xiaoye Qu et al.
Boosting Policy and Process Reward Models with Monte Carlo Tree Search in Open-Domain QA
Chi-Min Chan, Chunpu Xu, Junqi Zhu et al.
The Lessons of Developing Process Reward Models in Mathematical Reasoning
Zhenru Zhang, Chujie Zheng, Yangzhen Wu et al.
reWordBench: Benchmarking and Improving the Robustness of Reward Models with Transformed Inputs
Zhaofeng Wu, Michihiro Yasunaga, Andrew Cohen et al.
RAGferee: Building Contextual Reward Models for Retrieval-Augmented Generation
Andrei C. Coman, Ionut-Teodor Sorodoc, Leonardo F. R. Ribeiro et al.
Process-Supervised Reward Models for Verifying Clinical Note Generation: A Scalable Approach Guided by Domain Expertise
Hanyin Wang, Chufan Gao, Qiping Xu et al.
Logical Reasoning with Outcome Reward Models for Test-Time Scaling
Ramya Keerthy Thatikonda, Wray Buntine, Ehsan Shareghi