# LoOPSD: On-Policy Self-Distillation with Looped Teachers

Authors: Wei Fan, Qingyue Yang, Chao-Hong Tan, Qian Chen, Wen Wang, Xiangang Li, Kejiang Chen, Weiming Zhang, Nenghai Yu.

Searches for layers to repeat to make a stronger teacher from the current model, then distills its predictions into the original student. Repeats search and distillation as the student improves.

First public: 2026-10-13.
ArXiv initial submission: 2026-10-13.

[Original paper](https://arxiv.org/abs/2610.18162) · [Reading-list entry](https://latent-implicit-thinking.github.io/papers/2610.18162/)
[Preprint BibTeX](https://latent-implicit-thinking.github.io/papers/2610.18162/citation.bib) · [Preprint CSL-JSON](https://latent-implicit-thinking.github.io/papers/2610.18162/citation.csl.json) · [JSON record](https://latent-implicit-thinking.github.io/papers/2610.18162/record.json)

## Approaches

- [Recurrent reasoning](https://latent-implicit-thinking.github.io/topics/recurrent-reasoning/): Repeat parts of the model or keep intermediate information in memory while working through a problem. Some methods also learn how many passes to run.

Summary and categories are editorial. Read the original paper to verify claims and limitations. A citation to a paper does not, by itself, establish that a later method builds on it.

Reading-list version 0.9.5; literature checked through 2026-10-18.