RRepoGEO

REPOGEO REPORT · LITE

Yuliang-Liu/Monkey

Default branch main · commit 60c76060 · scanned 5/12/2026, 11:33:11 AM

GitHub: 1,951 stars · 140 forks

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 Yuliang-Liu/Monkey, 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 clear, disambiguating introductory sentence to the README

    Why:

    CURRENT
    The README currently starts with HTML tags and a centered H3 title.
    COPY-PASTE FIX
    Insert the following as the very first visible text in the README: `This is the official repository for **Monkey**, a Large Multi-modal Model (LMM) project focusing on high-resolution image and text integration, presented at CVPR 2024.`
  • hightopics#2
    Add relevant topics to the repository

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    large-multimodal-models, lmm, computer-vision, nlp, multimodal-ai, cvpr-2024, document-understanding, ocr-free
  • mediumhomepage#3
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://arxiv.org/abs/2311.06607

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/Monkey
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 1 of 2 queries
COMPETITOR LEADERBOARD
  1. GPT-4o · recommended 1×
  2. Gemini 1.5 Pro · recommended 1×
  3. llava-vl/LLaVA · recommended 1×
  4. THUDM/CogVLM · recommended 1×
  5. adept/fuyu-8b · recommended 1×
  • CATEGORY QUERY
    Looking for large multimodal models that excel at integrating high-resolution images with text.
    you: not recommended
    AI recommended (in order):
    1. GPT-4o
    2. Gemini 1.5 Pro
    3. LLaVA (llava-vl/LLaVA)
    4. CogVLM (THUDM/CogVLM)
    5. Fuyu-8B (adept/fuyu-8b)
    6. Qwen-VL-Max / Qwen-VL-Chat (QwenLM/Qwen-VL)

    AI recommended 6 alternatives but never named Yuliang-Liu/Monkey. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What AI solutions exist for OCR-free document understanding in large language models?
    you: not recommended
    AI recommended (in order):
    1. LayoutLMv1
    2. LayoutLMv2
    3. LayoutLMv3
    4. Donut
    5. Pix2Struct
    6. UDOP
    7. LiLT
    8. VisualBERT

    AI recommended 8 alternatives but never named Yuliang-Liu/Monkey. 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/Monkey?
    pass
    AI named Yuliang-Liu/Monkey explicitly

    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/Monkey in production, what risks or prerequisites should they evaluate first?
    pass
    AI named Yuliang-Liu/Monkey 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/Monkey solve, and who is the primary audience?
    pass
    AI named Yuliang-Liu/Monkey explicitly

    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/Monkey — 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