RRepoGEO

REPOGEO REPORT · LITE

haoranD/Awesome-Embodied-AI

Default branch main · commit a71d24dd · scanned 6/12/2026, 10:17:55 PM

GitHub: 525 stars · 26 forks

AI VISIBILITY SCORE
15 /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
0 / 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 haoranD/Awesome-Embodied-AI, 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 README's opening sentence to emphasize its role as a curated index

    Why:

    CURRENT
    A curated list of awesome papers on Embodied AI and related research/industry-driven resources, inspired by awesome-computer-vision.
    COPY-PASTE FIX
    This repository is a comprehensive, curated index of awesome papers and resources in Embodied AI, serving as a central hub for researchers and practitioners.
  • highhomepage#2
    Add repository URL as homepage

    Why:

    COPY-PASTE FIX
    https://github.com/haoranD/Awesome-Embodied-AI
  • mediumreadme#3
    Add a 'Why use this list?' or 'Value Proposition' section to README

    Why:

    COPY-PASTE FIX
    ## Why use this list?

Unlike general search engines or broad academic databases, Awesome-Embodied-AI provides a hand-picked, organized collection specifically focused on Embodied AI. We curate the most impactful papers, workshops, and resources, saving you time and ensuring you stay updated with the field's rapid advancements.

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 haoranD/Awesome-Embodied-AI
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. NeurIPS · recommended 1×
  4. ICML · recommended 1×
  5. ICLR · recommended 1×
  • CATEGORY QUERY
    Where can I find a comprehensive collection of cutting-edge research papers in embodied AI?
    you: not recommended
    AI recommended (in order):
    1. arXiv.org
    2. Google Scholar
    3. NeurIPS
    4. ICML
    5. ICLR
    6. RSS
    7. CoRL
    8. ICRA
    9. IROS
    10. Science Robotics
    11. Nature Machine Intelligence
    12. T-RO
    13. IJRR
    14. Papers With Code
    15. DeepMind
    16. Google Brain
    17. Meta AI
    18. OpenAI
    19. Stanford AI Lab
    20. MIT CSAIL
    21. Twitter/X

    AI recommended 21 alternatives but never named haoranD/Awesome-Embodied-AI. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the key resources and papers on LLM-driven embodied agents and robotics?
    you: not recommended
    AI recommended (in order):
    1. SayCan
    2. PaLM-E
    3. Inner Monologue
    4. Voyager
    5. RT-1
    6. Code as Policies

    AI recommended 6 alternatives but never named haoranD/Awesome-Embodied-AI. 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 haoranD/Awesome-Embodied-AI?
    pass
    AI did not name haoranD/Awesome-Embodied-AI — 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 haoranD/Awesome-Embodied-AI in production, what risks or prerequisites should they evaluate first?
    pass
    AI did not name haoranD/Awesome-Embodied-AI — 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?

  • In one sentence, what problem does the repo haoranD/Awesome-Embodied-AI solve, and who is the primary audience?
    pass
    AI did not name haoranD/Awesome-Embodied-AI — 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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haoranD/Awesome-Embodied-AI — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

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  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite