Author

Xue Yang

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#machine learning May 2026

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

Temperature-Scaled On-Policy Self-Distillation (TS-OPSD), a lightweight policy reheating method that internalizes the exploratory effect of temperature into model parameters, suggests that entropy restoration can serve as a simple post-collapse intervention for extending reasoning-oriented RL.

Xue Yang, Jiachen Yu, J. Wu et al. · arXiv.org · 1 citation

Preprint Aug 2026

Simple-OPD: Demystifying Warm-up for On-policy Distillation

It is found that effective warm-up relies on teacher-compatible chain-of-thought supervision, and that even incorrect teacher rollouts can provide comparable benefits to correct ones, which suggests that warm-up primarily transfers a teacher-compatible thinking pattern rather than merely correct answers.

Tao Liu, Taiqiang Wu, Mao Zheng et al. · 3 citations · ⚡1