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Wuhan University
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A frozen instruct model can reshape a student's reasoning policy, enabling RL refinement that surpasses traditional methods without costly fine-tuning.
Dynamic data mixing via loss trajectories boosts performance across tasks while using just 25% of the proxy compute budget.
