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arXiv Machine Learning By Xuewei Yang, Jiachen Yu, Jie Wu, Shaoning Sun, Junjie Wang, Yujiu Yang

Internalize the Temperature: On-Policy Self-Distillation as Policy Reheater for Reinforcement Learning

Read the original on arXiv Machine Learning →

arXiv:2606. 00755v1 Announce Type: cross Abstract: Reinforcement learning from verifiable rewards improves the reasoning ability of large language models, but often suffers from entropy collapse, in which increasingly concentrated policies reduce rollout diversity and useful learning signals.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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