SR-OPSD: Self-Referenced On-Policy Self-Distillation
On-policy self-distillation (OPSD) converts feedback into dense token-level supervision on trajectories generated by the policy to be optimized, providing a useful complement to reinforcement learning with sparse outcome rewards. However, the self-teacher policy used in OPSD is typically a stop-gradient or exponential-moving-average copy of the policy conditioned on additional context information, and thus co-evolves with both the student policy and its on-policy context distribution. Directly m
Record details
Published: 10 August 2026
Source: arXiv cs.AI
Category: Research
Topics: Regulation · Children & education
Retrieved: 11 August 2026
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ethics.ai (10 August 2026), “SR-OPSD: Self-Referenced On-Policy Self-Distillation,” evidence record 18261, https://ethics.ai/record/18261 (originally published by arXiv cs.AI).
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