Unverified50% confidenceFactExact time
The core of the R2S (Rollout-to-Scorer Distillation) method is to repair the teacher scorer before standard OPD so that its scores align with the teacher's takeover behavior.
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10/21/2026
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UnverifiedThe R2S pipeline has three steps: 1) starting from the untrained student model, mine the states where it diverges most from the teacher; 2) run teacher takeovers from these states and filter the takeover segments using reward-free checks (consensus or LLM judging); 3) fine-tune the teacher scorer on the filtered takeover data, then freeze it as the sole scorer for standard OPD.72% similarUnverifiedGAD-RL weights the forward KL divergence using the student's predicted probability for the teacher's Top-1 token, suppressing local auxiliary updates when the student's support for the teacher's recommended token is low63% similarUnverifiedThe core operation of SimOPD is to make the similarity distribution induced by the response representations output by the student model approach the similarity distribution induced by the teacher model's internal representations, using KL divergence or cross-entropy loss to bring the two distributions closer.60% similarUnverifiedBoth the PPO and RLCD approaches attempt to move away from the autoregressive paradigm and use reinforcement learning to produce structured probabilistic or confidence outputs.60% similarUnverifiedThe feedback loop of RLTL;DR is composed entirely of the agent itself and the validator, requiring neither teacher model distillation nor manually annotated example solutions.59% similar
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