RRepoGEO

REPOGEO REPORT · LITE

Yuliang-Liu/AWESOME-OCR-LLM

Default branch main · commit bcbd83e9 · scanned 6/30/2026, 8:28:00 PM

GitHub: 557 stars · 35 forks

AI VISIBILITY SCORE
22 /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
1 / 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 Yuliang-Liu/AWESOME-OCR-LLM, 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
  • hightopics#1
    Add specific topics to improve categorization

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    awesome-list, ocr, llm, large-language-models, document-understanding, research, reading-list, multimodal-llm
  • highabout#2
    Update GitHub description to clarify repo type

    Why:

    CURRENT
    OCR in the Era of Large Language Models
    COPY-PASTE FIX
    A curated reading list and resource hub for OCR research in the era of Large Language Models.
  • mediumhomepage#3
    Add a homepage URL to the repository metadata

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    https://github.com/Yuliang-Liu/AWESOME-OCR-LLM

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 Yuliang-Liu/AWESOME-OCR-LLM
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
PaddleOCR
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. PaddleOCR · recommended 1×
  2. Donut · recommended 1×
  3. LayoutLMv3 · recommended 1×
  4. Pix2Struct · recommended 1×
  5. GPT-4V · recommended 1×
  • CATEGORY QUERY
    Where can I find a comprehensive reading list for OCR research using large language models?
    you: not recommended
    AI recommended (in order):
    1. PaddleOCR

    AI recommended 1 alternative but never named Yuliang-Liu/AWESOME-OCR-LLM. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the latest research trends and models for document understanding with multimodal LLMs?
    you: not recommended
    AI recommended (in order):
    1. Donut
    2. LayoutLMv3
    3. Pix2Struct
    4. GPT-4V
    5. LLaVA
    6. UDOP
    7. LiLT
    8. mPLUG-DocVQA
    9. UReader

    AI recommended 9 alternatives but never named Yuliang-Liu/AWESOME-OCR-LLM. 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 Yuliang-Liu/AWESOME-OCR-LLM?
    pass
    AI did not name Yuliang-Liu/AWESOME-OCR-LLM — likely talking about a different project

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

  • If a team adopts Yuliang-Liu/AWESOME-OCR-LLM in production, what risks or prerequisites should they evaluate first?
    pass
    AI named Yuliang-Liu/AWESOME-OCR-LLM 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 Yuliang-Liu/AWESOME-OCR-LLM solve, and who is the primary audience?
    pass
    AI did not name Yuliang-Liu/AWESOME-OCR-LLM — likely talking about a different project

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

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Yuliang-Liu/AWESOME-OCR-LLM — 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