Unverified50% confidenceSolutionExact time
The 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.
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10/21/2026
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UnverifiedThe 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.72% similarUnverifiedThe ReDiST workflow consists of three steps: student-draft-based trace revision, student-matched filtering and ranking, and balanced distillation loss, all completed in the offline stage, with only the distilled student model used at inference time.69% similarUnverifiedThe endpoint-style policy distillation method uses the difference in log probabilities of the teacher model before and after RL training as the supervision signal, applied to trajectories generated by the student model itself.68% similarVerifiedRLHF was formally systematized by the InstructGPT paper in 2022, with a basic three-step process: collecting human preference data to train a reward model, optimizing the language model using reinforcement learning algorithms such as PPO, and continuous iteration.67% similarUnverifiedThe program mutation mechanism of RPL consists of three steps: sampling suboptimal programs, performing grammar-constrained mutation within predefined grammar rules, and actually running and validating them and distilling effective mutations into training trajectories back to the policy model.67% similar
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