Pass the Baton: Trajectory-Relayed On-Policy Distillation episode artwork

EPISODE · Jul 30, 2026 · 20 MIN

Pass the Baton: Trajectory-Relayed On-Policy Distillation

from Daily Paper Cast · host Jingwen Liang, Gengyu Wang

🤗 Upvotes: 24 | cs.CL, cs.AI Authors: Haolei Xu, Xiaowen Xu, Haiwen Hong, Zixuan Ni, Hongxing Li, Yiwen Qiu, Weiming Lu, Yongliang Shen Title: Pass the Baton: Trajectory-Relayed On-Policy Distillation Arxiv: http://arxiv.org/abs/2607.26057v1 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%.

Episode metadata supplied by the publisher feed · Published Jul 30, 2026

Embed this episode

NOW PLAYING

Pass the Baton: Trajectory-Relayed On-Policy Distillation

0:00 20:19

No transcript for this episode yet

We transcribe on demand. Request one and we'll notify you when it's ready — usually under 10 minutes.

No similar episodes found.

No similar podcasts found.

Frequently Asked Questions

How long is this episode of Daily Paper Cast?

This episode is 20 minutes long.

When was this Daily Paper Cast episode published?

This episode was published on July 30, 2026.

Can I download this Daily Paper Cast episode?

Yes. Use the download control on the episode player to save the publisher-provided media file.
URL copied to clipboard!