EvoRubric is proposed, a co-evolutionary RL framework that combines criterion-validity feedback, response discrimination, and peer agreement to learn rubrics for open-ended generation and improves over matched static and external evolving-rubric baselines across five benchmarks in Medical, Writing, and Science.
Analysis of rubric-grounded credit suggests more efficient evidence acquisition and higher-quality reports under limited research-turn budgets, motivating the extension of rubric-grounded process supervision to a broader range of rubric-based tasks.
Ying-Jian Zhu, Zhen-Yi Wang, Jia-Xing Guo et al.· 0 citations
This work introduces two exact, gradient-equivalent corrections: LogitTree, a segmented K-forward traversal, and a packed 4D attention mask, and proposes SDCC (Self-Distillation for Conditioning Consistency), a single-backward-pass variational relaxation.
J. Zinco, Xun-Jie Zhu, Shen Huang et al.· 0 citations
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