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cs.LG2026
Rubric Dropout: A Simple Way to Mitigate Reward Hacking in Rubric-Based RL
Minglai Yang, Xinyu Guo, Zhengliang Shi +8
Rubric-based reinforcement learning, in which an LLM judge scores responses against prompt-specific criteria, has become a standard way to post-train language models on tasks witho…
cs.LG2026
Rubric-Guided Self-Distillation: Post-Training Without Rubric Verifiers
MohammadHossein Rezaei, Anas Mahmoud, Zihao Wang +6
Rubrics have emerged as an alternative to RLVR in open-ended domains where a single ground-truth final answer is not available. Existing rubric-based training methods rely on an LL…