RRepoGEO

REPOGEO REPORT · LITE

Hub-Tian/UAVs_Meet_LLMs

Default branch main · commit 752a8967 · scanned 7/1/2026, 6:03:43 PM

GitHub: 500 stars · 46 forks

AI VISIBILITY SCORE
23 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 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 Hub-Tian/UAVs_Meet_LLMs, 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

2 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highabout#1
    Add a concise repository description

    Why:

    COPY-PASTE FIX
    An active repository exploring the synergy between Unmanned Aerial Vehicles (UAVs) and Large Language Models (LLMs), featuring overviews, papers, and perspectives toward agentic low-altitude mobility.
  • mediumhomepage#2
    Add the official paper URL as the repository homepage

    Why:

    COPY-PASTE FIX
    Once available, add the official URL for the paper 'UAVs Meet LLMs: Overviews and Perspectives Toward Agentic Low-Altitude Mobility' accepted by *Information Fusion*.

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 Hub-Tian/UAVs_Meet_LLMs
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
OpenAI GPT-4
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. OpenAI GPT-4 · recommended 1×
  2. GPT-3.5 Turbo · recommended 1×
  3. Hugging Face Transformers · recommended 1×
  4. Llama 3 · recommended 1×
  5. Mistral · recommended 1×
  • CATEGORY QUERY
    How can I use large language models to enhance the autonomy of unmanned aerial vehicles?
    you: not recommended
    AI recommended (in order):
    1. OpenAI GPT-4
    2. GPT-3.5 Turbo
    3. Hugging Face Transformers
    4. Llama 3
    5. Mistral
    6. LangChain
    7. LlamaIndex
    8. GPT-4o
    9. LLaVA
    10. Google Gemini Pro Vision
    11. YOLO
    12. Detectron2
    13. Claude 3 Opus
    14. Microsoft Guidance
    15. Stable Baselines3
    16. Ray RLlib
    17. Claude 3 Sonnet
    18. Streamlit
    19. Gradio
    20. vLLM
    21. NVIDIA TensorRT-LLM
    22. Apache Kafka
    23. RabbitMQ

    AI recommended 23 alternatives but never named Hub-Tian/UAVs_Meet_LLMs. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What frameworks exist for developing agentic drone systems with advanced AI capabilities?
    you: not recommended
    AI recommended (in order):
    1. ROS 2
    2. PX4 Autopilot (PX4/PX4-Autopilot)
    3. MAVLink (mavlink/mavlink)
    4. MAVSDK (mavlink/MAVSDK)
    5. TensorFlow (tensorflow/tensorflow)
    6. PyTorch (pytorch/pytorch)
    7. OpenCV (opencv/opencv)
    8. RLlib (ray-project/ray)
    9. NVIDIA JetPack SDK

    AI recommended 9 alternatives but never named Hub-Tian/UAVs_Meet_LLMs. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    fail

    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 Hub-Tian/UAVs_Meet_LLMs?
    pass
    AI named Hub-Tian/UAVs_Meet_LLMs explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts Hub-Tian/UAVs_Meet_LLMs in production, what risks or prerequisites should they evaluate first?
    pass
    AI named Hub-Tian/UAVs_Meet_LLMs 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 Hub-Tian/UAVs_Meet_LLMs solve, and who is the primary audience?
    pass
    AI did not name Hub-Tian/UAVs_Meet_LLMs — 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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Hub-Tian/UAVs_Meet_LLMs — 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