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Overcoming Scaling Limits in On-Policy Self-Distillation for LLM Reasoning
On-policy self-distillation (OPSD) trains a student to match a privileged teacher distribution along its own sampled trajectory. Standard OPSD applies this supervision to unverified student rollouts while conditioning the teacher on privileged context, typically a reference solution. We separate the
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