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cs.LG2026
Scoring Higher, Answering Worse: Mitigating Reward Hacking in Rubric-Based RL via Protocol-Level Rubrics
Maoqi Liu, Junwei He, Bowen Zhang +5
Rubric-based reinforcement learning (Rubric-RL) trains language models where no verifier exists. A judge checks each criterion of a rubric, and the verdicts are aggregated into a r…
cs.LG2025
InCo-DPO: Balancing Distribution Shift and Data Quality for Enhanced Preference Optimization
Yunan Wang, Jijie Li, Bo-Wen Zhang +2
Direct Preference Optimization (DPO) optimizes language models to align with human preferences. Utilizing on-policy samples, generated directly by the policy model, typically resul…