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About this paper
Yuhang Zhou, Yifan Wu, Bo Peng, Mingyi Wang, Jiayi Liu, Xiangjun Fan, Lizhu Zhang, Zhuokai Zhao
RSD trains an agent by having the same model retrospectively re-score its completed actions using accumulated experience and hindsight unavailable during acting, then distilling those judgments into the policy. Its core update needs neither ground-truth trajectories nor verifier-derived rewards. On ScienceWorld, Qwen3-8B reaches 23.4 development task-success rate versus 15.6 for the base model, though gains vary by task.
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