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arxiv:2607.26057

Pass the Baton: Trajectory-Relayed On-Policy Distillation

Published on Jul 28
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on Jul 29
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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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We introduce Relay-OPD ๐Ÿƒ โ€” on-policy distillation that fixes prefix failure: once a student commits to a wrong reasoning direction early, the entire rollout builds on the mistake, yielding unreliable supervision and wasted compute.

Key observation: on failed prefixes, teacher and student diverge โ€” the teacher wants to stop and redirect ("But", "Wait"โ€ฆ), while the student presses on. This divergence is observable online, with no verifier, reward model, or labels, and it marks exactly where to intervene. Relay-OPD lets the teacher briefly take over at these handoff triggers, then pass the baton back to the student, with a relay budget keeping intervention early and local. The entire rollout runs in a single speculative-decoding engine (student drafts, teacher verifies).

Results: with a Qwen3-4B teacher and 0.6B/1.7B students on 8 math reasoning benchmarks: +5.73% avg. over standard OPD, +1.49% over the strongest baseline FastOPD, while cutting training trajectory length by >50%.

๐Ÿ’ป Code: https://github.com/ZJU-REAL/Relay-OPD
๐ŸŒ Project: https://zju-real.github.io/Relay-OPD/

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