# Multimodal Latent Language Modeling with Next-Token Diffusion

Authors: Yutao Sun, Hangbo Bao, Wenhui Wang, Zhiliang Peng, Li Dong, Shaohan Huang, Jianyong Wang, Furu Wei.

Encodes continuous data such as images as vectors, then generates those vectors with diffusion inside a causal transformer. This is related work on multimodal generation, rather than a method trained directly on reasoning steps.

First public: 2024-12-11.
ArXiv initial submission: 2024-12-11.

[Original paper](https://arxiv.org/abs/2412.08635) · [Reading-list entry](https://latent-implicit-thinking.github.io/papers/2412.08635/)
[Preprint BibTeX](https://latent-implicit-thinking.github.io/papers/2412.08635/citation.bib) · [Preprint CSL-JSON](https://latent-implicit-thinking.github.io/papers/2412.08635/citation.csl.json) · [JSON record](https://latent-implicit-thinking.github.io/papers/2412.08635/record.json)

## Approaches

- [Alternative generation methods](https://latent-implicit-thinking.github.io/topics/alternative-reasoning-schedules/): Change how intermediate steps are generated, revised, or searched—for example, by refining several steps in parallel. These are related approaches: some still produce written chains of thought.

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.