# LoopVL: Recurrent Visual Intelligence

Authors: Zhe Qian, Ziyang Gong, Zhongxing Xu, Hehan Li, Zhonghua Wang, Hanmeng Liu, Liwei Qian, Xin Pei, Peizhi Xu, Fei Luo, Mingxuan Wang, Xue Yang, Shiwei Liu, Yanbiao Ma, Junchi Yan, Jungong Han.

Extends shared-module and whole-model looping to vision-language models, repeatedly updating a joint visual-language state. Trains from scratch through language and multimodal stages and evaluates visual understanding and reasoning.

First public: 2026-09-29.
ArXiv initial submission: 2026-09-29.

[Original paper](https://arxiv.org/abs/2609.38426) · [Reading-list entry](https://latent-implicit-thinking.github.io/papers/2609.38426/)
[Preprint BibTeX](https://latent-implicit-thinking.github.io/papers/2609.38426/citation.bib) · [Preprint CSL-JSON](https://latent-implicit-thinking.github.io/papers/2609.38426/citation.csl.json) · [JSON record](https://latent-implicit-thinking.github.io/papers/2609.38426/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.