EvoRubric: Self-Evolving Rubric-Driven RL for Open-Ended Generation 事件

EvoRubric: Self-Evolving Rubric-Driven RL for Open-Ended Generation arXiv:2605.29847v1 Announce Type: new Abstract: Reinforcement Learning (RL) has significantly advanced Large Language Models (LLMs) in verifiable domains, but aligning models for open-ended generation remains profoundly challenging due to the lack of definitive rewards. Current rubric-based RL methods mitigate this by employing explicit criteria; however, they rely heavily on static, human-annotated rubrics that inevitably caus