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When Importance Sampling Misallocates Credit: Asymmetric Ratios for Outcome-Supervised RL
最新研究揭示重要性采样在结果监督RL中的信用分配偏差，提出不对称比率改进方法，为LLM后训练提供新视角。
arXiv:2510.06062v2 Announce Type: replace Abstract: Reinforcement learning (RL) has shown great promise in large language models (LLMs) post-training,…