Pass the Baton: Trajectory-Relayed On-Policy Distillation

Haolei Xu, Xiaowen Xu, Haiwen Hong, Zixuan Ni, Hongxing Li +3 more
7/28/2026
cs.CLcs.AI

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Abstract

On-policy distillation (OPD) grounds token-level supervision in the student's own trajectory, yet suffers from prefix failure: once the student commits to a wrong reasoning direction, all subsequent generation builds on this deviation, producing misdirected continuations that elicit unreliable supervision and waste compute. We identify a teacher-student continuation asymmetry on failed prefixes, where the teacher tends to redirect while the student continues along the original direction, and convert it into a label-free handoff trigger in Relay On-Policy Distillation (Relay-OPD). During training, Relay-OPD constructs relay trajectories by letting the teacher briefly take over at detected trigger points to produce a teacher leg, after which the student resumes and is optimized on the resulting trajectory. A limited relay budget concentrates intervention on critical early positions while limiting departure from the student policy. With a Qwen3-4B-Instruct-2507 teacher and Qwen3-0.6B/1.7B-Non-Thinking students on eight mathematical reasoning benchmarks, Relay-OPD achieves the best or second-best results on every benchmark, outperforming standard OPD by +5.73% and the strongest baseline FastOPD by +1.49% on average for 1.7B, with consistent gains at 0.6B. Training trajectory length is reduced by over 50%.

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Cite this paper

@article{xu2026pass,
  title  = {Pass the Baton: Trajectory-Relayed On-Policy Distillation},
  author = {Haolei Xu and Xiaowen Xu and Haiwen Hong and Zixuan Ni and Hongxing Li and Yiwen Qiu and Weiming Lu and Yongliang Shen},
  year   = {2026},
  eprint = {2607.26057},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2607.26057v1}
}

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