Eval-Skill
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Beyond Rubrics: Exploration-Guided Evaluation Skills for Reward Modeling
arXiv:2606.07040v1 Announce Type: new Abstract: Open-ended reward modeling requires judges that can follow subtle, domain-specific preferences when verifiable answers are unavailable. Existing rubric-based methods often address this by generating criteria online for each query, but the extra generation step can add inference overhead and produce rigid or misaligned guidance. We introduce Eval-Skill, an exploration-guided method that synthesizes reusable evaluation skills for reward modeling...