RL Starts before RL: On Policy Distillation for Better Reinforcement Learning
Reinforcement learning (RL) improves reasoning, but its performance depends on the policy from which training begins. We study on-policy distillation (OPD) as a preparation stage for RL and ask whether its benefits extend beyond improvements in the distilled model's initial accuracy. Under shared RL settings, students...
Shuai Dong, Yong-Fu Zhu, Yu-Qi Xu et al.
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