# opendatalab/MinerU-Diffusion

<https://repo.masters-masters.com/en/repos/opendatalab/MinerU-Diffusion>

[Home](https://repo.masters-masters.com/en) › [opendatalab](https://repo.masters-masters.com/en/owners/opendatalab) › [MinerU-Diffusion](https://repo.masters-masters.com/en/repos/opendatalab/MinerU-Diffusion)

opendatalab/MinerU-Diffusion has 623 stars on GitHub. Its RepoMasters card: Alpha tier. \[ECCV 2026\] A diffusion-based framework for document OCR that replaces…

| Field | Value |
| --- | --- |
| Owner | [opendatalab](https://repo.masters-masters.com/en/owners/opendatalab) |
| Stars | 623 |
| Forks | 42 |
| Language | [Python](https://repo.masters-masters.com/en/languages/python) |
| License | MIT |
| Created | 2026 |
| Topics | ai4science, diffusion, dlm, document-analysis, extract-data, layout-analysis, llada, ocr, parser, pdf |
| Tier | [Alpha (250 to 699 ★)](https://repo.masters-masters.com/en/ranks/b_movie) |
| View on GitHub | [opendatalab/MinerU-Diffusion](https://github.com/opendatalab/MinerU-Diffusion) |

## Repository

\[ECCV 2026\] A diffusion-based framework for document OCR that replaces autoregressive decoding with block-level parallel diffusion decoding.

The tier for repos with 250 to 699 ★. Published odds per card pulled: 20%. Rarity: Uncommon.

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Data: GitHub · Illustration drawn by RepoMasters from the repo’s ID and its language color.