Rubrics on Trial: Evolving Rubrics from a Single Query via Synthetic Pairwise Evidence
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 identifies the better of two rubrics and guides the direction of evolution. However, accurate rubric comparison is difficult, which presents two challenges. (1) It should reflect downstream task performance, which is essential for assessing rubric utility but often prohibitively expensive to evaluate. (2) It should discourage unnecessary criteria, which increase verification costs and may dilute the influence of essential criteria. To address these challenges, we introduce Rubrics on Trial, a multi-agent framework t...
| Authors | Haocheng Yang, Licheng Pan, Yuan Lu et al. |
|---|---|
| Primary category | cs.CL |
| Published | 16 July 2026 |
| Last updated at source | 5 October 2026 |
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