RRepoGEO

REPOGEO REPORT · LITE

leofan90/Awesome-World-Models

Default branch main · commit f8d4b6f2 · scanned 6/21/2026, 6:32:51 AM

GitHub: 1,815 stars · 60 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)

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

AI VISIBILITY SCORE
28 /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
2 / 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
    Clarify the repo's nature as an 'Awesome List' in the README's opening

    Why:

    CURRENT
    This repository provides a curated list of **papers for World Models for General Video Generation, Embodied AI, and Autonomous Driving**.
    COPY-PASTE FIX
    This **Awesome List** is a comprehensive, curated collection of **papers, code, and related websites** focused on **World Models for General Video Generation, Embodied AI, and Autonomous Driving**.
  • mediumabout#2
    Update the GitHub 'About' description to explicitly state it's an 'Awesome List'

    Why:

    CURRENT
    A comprehensive list of papers for the definition of World Models and using World Models for General Video Generation, Embodied AI, and Autonomous Driving, including papers, codes, and related websites.
    COPY-PASTE FIX
    An **Awesome List**: a comprehensive, curated collection of papers, code, and resources on World Models for General Video Generation, Embodied AI, and Autonomous Driving.
  • lowhomepage#3
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://github.com/leofan90/Awesome-World-Models

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
Google Scholar
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Google Scholar · recommended 1×
  2. arXiv · recommended 1×
  3. NeurIPS · recommended 1×
  4. ICML · recommended 1×
  5. ICLR · recommended 1×
  • CATEGORY QUERY
    Where can I find academic papers on world models for embodied AI and autonomous driving?
    you: not recommended
    AI recommended (in order):
    1. Google Scholar
    2. arXiv
    3. NeurIPS
    4. ICML
    5. ICLR
    6. CVPR
    7. ICRA
    8. IROS
    9. RSS
    10. IEEE Xplore Digital Library
    11. ACM Digital Library
    12. SpringerLink
    13. ScienceDirect
    14. Elsevier
    15. International Journal of Robotics Research
    16. Robotics and Autonomous Systems
    17. IEEE Transactions on Robotics
    18. Journal of Machine Learning Research
    19. DeepMind
    20. OpenAI
    21. Stanford AI Lab
    22. MIT CSAIL
    23. UC Berkeley AI Research

    AI recommended 23 alternatives but never named leofan90/Awesome-World-Models. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What resources exist for understanding future prediction in video generation using deep learning?
    you: not recommended
    AI recommended (in order):
    1. VideoGPT
    2. DVD-GAN
    3. PredNet
    4. Learning to Predict Future Frames by Learning to Inpaint
    5. Video Diffusion Models
    6. Phenaki
    7. PyTorchVideo

    AI recommended 7 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 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?

  • 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.

  • Deep reports10 / month
  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite