RRepoGEO

REPOGEO REPORT · LITE

leofan90/Awesome-World-Models

Default branch main · commit c518029b · scanned 5/11/2026, 3:42:46 AM

GitHub: 1,625 stars · 52 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 leofan90/Awesome-World-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
  • highreadme#1
    Reposition the README H1 to reflect the full scope of the collection

    Why:

    CURRENT
    # Awesome World Models for Robotics
    COPY-PASTE FIX
    # Awesome World Models: Papers & Resources
  • mediumabout#2
    Add a homepage URL to the About section

    Why:

    COPY-PASTE FIX
    https://github.com/leofan90/Awesome-World-Models
  • lowtopics#3
    Add more specific topics to emphasize its nature as a curated paper list

    Why:

    CURRENT
    artificial-intelligence, autonomous-driving, awesome, deep-learning, embodied-ai, future-prediction, video-prediction, world-model
    COPY-PASTE FIX
    artificial-intelligence, autonomous-driving, awesome, deep-learning, embodied-ai, future-prediction, video-prediction, world-model, paper-list, research-papers

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 leofan90/Awesome-World-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. Google Scholar · recommended 1×
  3. IEEE Xplore Digital Library · recommended 1×
  4. ICRA · recommended 1×
  5. IROS · recommended 1×
  • CATEGORY QUERY
    Where can I find academic papers on world models for autonomous driving applications?
    you: not recommended
    AI recommended (in order):
    1. arXiv.org
    2. Google Scholar
    3. IEEE Xplore Digital Library
    4. ICRA
    5. IROS
    6. IV
    7. IEEE Transactions on Robotics
    8. IEEE Transactions on Intelligent Transportation Systems
    9. ACM Digital Library
    10. NeurIPS
    11. ICML
    12. CVPR
    13. OpenReview.net
    14. ICLR
    15. Semantic Scholar
    16. Mendeley
    17. Zotero

    AI recommended 17 alternatives but never named leofan90/Awesome-World-Models. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for comprehensive resources on world model architectures for advanced embodied AI systems.
    you: not recommended
    AI recommended (in order):
    1. DreamerV3
    2. DreamerV2
    3. DreamerV1
    4. World Models
    5. PlaNet
    6. MuZero
    7. SimPLe
    8. IRL
    9. Hindsight Experience Replay (HER)
    10. Rapidly-exploring Random Tree (RRT)

    AI recommended 10 alternatives but never named leofan90/Awesome-World-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 leofan90/Awesome-World-Models?
    pass
    AI did not name leofan90/Awesome-World-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 leofan90/Awesome-World-Models in production, what risks or prerequisites should they evaluate first?
    pass
    AI named leofan90/Awesome-World-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 leofan90/Awesome-World-Models solve, and who is the primary audience?
    pass
    AI did not name leofan90/Awesome-World-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?

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leofan90/Awesome-World-Models — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

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  • Brand-free category queries5 vs 2 in Lite
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