RRepoGEO

REPOGEO REPORT · LITE

X-PLUG/mPLUG-DocOwl

Default branch main · commit f91a7685 · scanned 6/26/2026, 12:38:06 AM

GitHub: 2,407 stars · 153 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

3 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE
35 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 1 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 X-PLUG/mPLUG-DocOwl, 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 concise problem/solution statement at the top of the README

    Why:

    CURRENT
    The README currently starts with a "News" section after the main title.
    COPY-PASTE FIX
    Insert the following paragraph directly after the main title and before the "News" section:
"mPLUG-DocOwl is a modularized multimodal large language model (MLLM) specifically designed for advanced OCR-free document understanding, information extraction, and complex reasoning across diverse document types, including charts and tables. It excels at processing multipage documents efficiently, making it ideal for researchers and developers building intelligent document processing systems."
  • mediumhomepage#2
    Add a homepage URL to the repository's About section

    Why:

    COPY-PASTE FIX
    Add the official project page or a relevant academic paper link (e.g., the arXiv link for the paper) to the repository's homepage field in the About section.
  • lowtopics#3
    Expand repository topics with more specific keywords

    Why:

    CURRENT
    chart-understanding, document-understanding, mllm, multimodal, multimodal-large-language-models, table-understanding
    COPY-PASTE FIX
    chart-understanding, document-understanding, mllm, multimodal, multimodal-large-language-models, table-understanding, information-extraction, document-ai, visual-question-answering

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 X-PLUG/mPLUG-DocOwl
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
GPT-4o
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. GPT-4o · recommended 2×
  2. Gemini 1.5 Pro · recommended 1×
  3. Claude 3 Opus/Sonnet · recommended 1×
  4. haotian-liu/LLaVA · recommended 1×
  5. clovaai/donut · recommended 1×
  • CATEGORY QUERY
    What multimodal large language models are effective for OCR-free document understanding and information extraction?
    you: not recommended
    AI recommended (in order):
    1. GPT-4o
    2. Gemini 1.5 Pro
    3. Claude 3 Opus/Sonnet
    4. LLaVA (haotian-liu/LLaVA)
    5. Donut (clovaai/donut)
    6. Nougat (facebookresearch/nougat)

    AI recommended 6 alternatives but never named X-PLUG/mPLUG-DocOwl. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a multimodal AI model to accurately interpret and extract data from charts and tables.
    you: not recommended
    AI recommended (in order):
    1. GPT-4o
    2. Google Gemini
    3. Claude 3 Opus
    4. Azure AI Document Intelligence
    5. Amazon Textract
    6. Nougat
    7. Donut

    AI recommended 7 alternatives but never named X-PLUG/mPLUG-DocOwl. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    warn

    Suggestion:

  • 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 X-PLUG/mPLUG-DocOwl?
    pass
    AI named X-PLUG/mPLUG-DocOwl explicitly

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

  • If a team adopts X-PLUG/mPLUG-DocOwl in production, what risks or prerequisites should they evaluate first?
    pass
    AI named X-PLUG/mPLUG-DocOwl 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 X-PLUG/mPLUG-DocOwl solve, and who is the primary audience?
    pass
    AI named X-PLUG/mPLUG-DocOwl 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 X-PLUG/mPLUG-DocOwl. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

RepoGEO badge previewLive preview
MARKDOWN (README)
[![RepoGEO](https://repogeo.com/badge/X-PLUG/mPLUG-DocOwl.svg)](https://repogeo.com/en/r/X-PLUG/mPLUG-DocOwl)
HTML
<a href="https://repogeo.com/en/r/X-PLUG/mPLUG-DocOwl"><img src="https://repogeo.com/badge/X-PLUG/mPLUG-DocOwl.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

X-PLUG/mPLUG-DocOwl — 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