Rubrics on Trial: Evolving Rubrics from a Single Query via Synthetic Pairwise Evidence
Rubrics provide structured, fine-grained signals for training and evaluating large language models (LLMs). Yet reliable query-specific rubrics are difficult to construct. Existing approaches often derive supervision from human-written rubrics, preference data, or sampled responses. Direct query-to-rubric generation avo...
Hao Yang, Licheng Pan, Xiaoxi Li et al.
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