RRepoGEO

REPOGEO REPORT · LITE

AIDC-AI/Awesome-Unified-Multimodal-Models

Default branch main · commit c81ef568 · scanned 5/8/2026, 5:13:11 PM

GitHub: 1,236 stars · 39 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 AIDC-AI/Awesome-Unified-Multimodal-Models, 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
  • highabout#1
    Update the GitHub repository description

    Why:

    CURRENT
    Awesome Unified Multimodal Models
    COPY-PASTE FIX
    A comprehensive, curated list and survey of unified multimodal models, including architectures, benchmarks, and resources.
  • highlicense#2
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    Create a LICENSE file (e.g., MIT or Apache-2.0) in the repository root.
  • mediumhomepage#3
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    Add `https://arxiv.org/abs/2505.02567` as the repository's homepage URL.

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 AIDC-AI/Awesome-Unified-Multimodal-Models
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
arXiv.org
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. arXiv.org · recommended 1×
  2. Papers With Code · recommended 1×
  3. Hugging Face · recommended 1×
  4. Google AI Blog · recommended 1×
  5. Meta AI Blog · recommended 1×
  • CATEGORY QUERY
    Where can I find a comprehensive survey of unified multimodal AI models?
    you: not recommended
    AI recommended (in order):
    1. arXiv.org
    2. Papers With Code
    3. Hugging Face
    4. Google AI Blog
    5. Meta AI Blog
    6. Microsoft Research Blog
    7. Towards Data Science
    8. Medium
    9. NeurIPS
    10. ICML
    11. CVPR
    12. ACL
    13. Wikipedia
    14. Scholarpedia

    AI recommended 14 alternatives but never named AIDC-AI/Awesome-Unified-Multimodal-Models. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What frameworks support any-to-any multimodal AI for various inputs like audio and video?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Transformers
    2. PyTorch Lightning
    3. TensorFlow / Keras
    4. DeepMind Perceiver IO
    5. OpenMMLab
    6. MMAction2
    7. MMEngine
    8. Fairseq

    AI recommended 8 alternatives but never named AIDC-AI/Awesome-Unified-Multimodal-Models. 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 AIDC-AI/Awesome-Unified-Multimodal-Models?
    pass
    AI did not name AIDC-AI/Awesome-Unified-Multimodal-Models — 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 AIDC-AI/Awesome-Unified-Multimodal-Models in production, what risks or prerequisites should they evaluate first?
    pass
    AI named AIDC-AI/Awesome-Unified-Multimodal-Models 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 AIDC-AI/Awesome-Unified-Multimodal-Models solve, and who is the primary audience?
    pass
    AI did not name AIDC-AI/Awesome-Unified-Multimodal-Models — 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?

Embed your GEO score

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  • Brand-free category queries5 vs 2 in Lite
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