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cs.CL2026
Rubrics on Trial: Evolving Rubrics from a Single Query via Synthetic Pairwise Evidence
Haocheng Yang, Licheng Pan, Xiaoxi Li +8
Rubric evolution offers a promising approach to improving the quality of rubrics generated by large language models (LLMs). Central to this process is rubric comparison, which iden…
cs.CL2026
Unbiased Reward Modeling from Implicit Feedback for LLM Alignment
Hao Wang, Haocheng Yang, Licheng Pan +7
Despite the success of reinforcement learning from human feedback (RLHF), existing reward modeling methods largely rely on explicit feedback, which is costly to collect and difficu…