Multi-Turn On-Policy Distillation with Prefix Replay
We study on-policy distillation (OPD) for agentic tasks, where an LLM agent interacts with an environment over multiple turns and a student imitates a teacher over these multi-turn interaction histories. Fully online OPD is costly because each update requires fresh student rollouts through the environment and teacher queries at visited histories. We propose Replayed-Prefix On-Policy Distillation (ReOPD), an off-environment alternative that reuses pre-collected teacher trajectories as replayed pr
Record details
Published: 15 July 2026
Source: HuggingFace Daily Papers
Category: Research
Topics: Regulation · Children & education · Agents & autonomy · Environment
Retrieved: 25 July 2026
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ethics.ai (15 July 2026), “Multi-Turn On-Policy Distillation with Prefix Replay,” evidence record 13009, https://ethics.ai/record/13009 (originally published by HuggingFace Daily Papers).
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