RRepoGEO

REPOGEO REPORT · LITE

opendatalab/MinerU-Diffusion

Default branch main · commit 8d456f1a · scanned 6/13/2026, 6:42:38 AM

GitHub: 597 stars · 38 forks

AI VISIBILITY SCORE
40 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
2 pass · 0 warn · 0 fail
Objective metadata checks
AI knows your name
3 / 3
Direct prompts that named your repo
HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface opendatalab/MinerU-Diffusion, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highreadme#1
    Add a direct, benefit-oriented summary sentence at the very top of the README

    Why:

    CURRENT
    The README starts with <p align="center"> and various links before the main H1 title.
    COPY-PASTE FIX
    MinerU-Diffusion is a 2.5B diffusion-based framework for document OCR that replaces autoregressive decoding with block-level parallel diffusion decoding, offering an efficient and reliable solution for document analysis.
  • mediumreadme#2
    Create a 'Key Features' or 'Why MinerU-Diffusion?' section in the README

    Why:

    COPY-PASTE FIX
    ## ✨ Key Features

*   **Diffusion-based OCR:** Leverages advanced diffusion models for robust document OCR.
*   **Block-level Parallel Decoding:** Achieves significantly faster OCR speeds compared to traditional autoregressive methods.
*   **Inverse Rendering Approach:** Rethinks document OCR as an inverse rendering problem, enhancing control and interpretability.
*   **2.5B Parameter Model:** Provides a powerful and reliable framework for complex document analysis.
  • lowhomepage#3
    Update the Homepage metadata to a more interactive resource

    Why:

    CURRENT
    https://arxiv.org/pdf/2603.22458
    COPY-PASTE FIX
    https://huggingface.co/spaces/opendatalab/MinerU-Diffusion-V1-0320-2.5B

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall
0 / 2
0% of queries surface opendatalab/MinerU-Diffusion
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Google Cloud Document AI
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Google Cloud Document AI · recommended 2×
  2. Amazon Textract · recommended 2×
  3. PaddleOCR · recommended 1×
  4. Donut · recommended 1×
  5. Pix2Struct · recommended 1×
  • CATEGORY QUERY
    Need an efficient OCR solution for document analysis using diffusion models.
    you: not recommended
    AI recommended (in order):
    1. PaddleOCR
    2. Donut
    3. Pix2Struct
    4. Tesseract OCR
    5. Google Cloud Document AI
    6. Amazon Textract

    AI recommended 6 alternatives but never named opendatalab/MinerU-Diffusion. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a fast document parser that leverages parallel decoding for improved OCR speed.
    you: not recommended
    AI recommended (in order):
    1. Google Cloud Document AI
    2. Amazon Textract
    3. Microsoft Azure Form Recognizer
    4. Tesseract OCR (tesseract-ocr/tesseract)
    5. ABBYY FineReader Engine SDK
    6. Kofax OmniPage Capture SDK

    AI recommended 6 alternatives but never named opendatalab/MinerU-Diffusion. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    pass

  • README presence
    pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

  • Compared to common alternatives in this category, what is the core differentiator of opendatalab/MinerU-Diffusion?
    pass
    AI named opendatalab/MinerU-Diffusion explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts opendatalab/MinerU-Diffusion in production, what risks or prerequisites should they evaluate first?
    pass
    AI named opendatalab/MinerU-Diffusion explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • In one sentence, what problem does the repo opendatalab/MinerU-Diffusion solve, and who is the primary audience?
    pass
    AI named opendatalab/MinerU-Diffusion explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

Embed your GEO score

Drop this badge into the README of opendatalab/MinerU-Diffusion. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

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MARKDOWN (README)
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opendatalab/MinerU-Diffusion — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

  • Deep reports10 / month
  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite