# Reliable Parallel Decoding in Masked Diffusion Language Models

Authors: Zhenghao He, Bohan Liu, Guangzhi Xiong, Aidong Zhang.

Studies when simultaneously committing several predicted tokens breaks their reasoning dependencies. RPD combines stability across final layers with confidence and uncertainty in preceding positions to defer unsupported predictions while retaining parallel text generation.

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

[Original paper](https://arxiv.org/abs/2609.36452) · [Reading-list entry](https://latent-implicit-thinking.github.io/papers/2609.36452/)
[Preprint BibTeX](https://latent-implicit-thinking.github.io/papers/2609.36452/citation.bib) · [Preprint CSL-JSON](https://latent-implicit-thinking.github.io/papers/2609.36452/citation.csl.json) · [JSON record](https://latent-implicit-thinking.github.io/papers/2609.36452/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.
- [Analysis and evaluation](https://latent-implicit-thinking.github.io/topics/implicit-reasoning-evaluation/): Measure how well these methods work, investigate what their internal computation does, and identify where they fail. This includes experiments, studies of model internals, and mathematical results.

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.