on-policy-reasoning-compression

【效率与协作】Compress verbose reasoning by conditioning the same model on a conciseness instruction to create a teacher. Minimize KL divergence between student outputs and concise teacher without ground truth, enabling implicit reward learning that improves accuracy while reducing tokens.

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