RRepoGEO

REPOGEO REPORT · LITE

opendilab/LMDrive

Default branch main · commit 308d8da0 · scanned 6/15/2026, 11:08:59 AM

GitHub: 906 stars · 75 forks

AI VISIBILITY SCORE
35 /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
3 / 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 opendilab/LMDrive, 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
  • hightopics#1
    Add relevant GitHub topics for discoverability

    Why:

    COPY-PASTE FIX
    ['autonomous-driving', 'large-language-models', 'llm', 'end-to-end-driving', 'cvpr-2024', 'robotics', 'computer-vision']
  • highreadme#2
    Clarify README's opening sentence to emphasize autonomous driving

    Why:

    CURRENT
    *An end-to-end, closed-loop, language-based autonomous driving framework, which interacts with the dynamic environment via multi-modal multi-view sensor data and natural language instructions.*
    COPY-PASTE FIX
    LMDrive is an end-to-end, closed-loop autonomous driving framework that leverages large language models to interpret multi-modal sensor data and natural language instructions.
  • mediumhomepage#3
    Populate the repository homepage URL

    Why:

    COPY-PASTE FIX
    Add the URL for the 'Project Page' linked in your README to the repository's homepage field.

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 opendilab/LMDrive
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
NVIDIA DriveWorks
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. NVIDIA DriveWorks · recommended 2×
  2. DriveGPT · recommended 1×
  3. Llama 3 · recommended 1×
  4. GPT-4 · recommended 1×
  5. Claude 3 · recommended 1×
  • CATEGORY QUERY
    How can I implement an end-to-end autonomous driving system using large language models?
    you: not recommended
    AI recommended (in order):
    1. DriveGPT
    2. Llama 3
    3. GPT-4
    4. Claude 3
    5. Hugging Face Transformers Library
    6. PyTorch
    7. TensorFlow
    8. CARLA
    9. ROS 2
    10. NVIDIA DriveWorks
    11. NVIDIA Drive AGX

    AI recommended 11 alternatives but never named opendilab/LMDrive. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a framework for closed-loop autonomous driving that interprets natural language instructions and sensor data.
    you: not recommended
    AI recommended (in order):
    1. NVIDIA DriveWorks
    2. NVIDIA Drive AGX Platform
    3. Riva
    4. Apollo (baidu/apollo)
    5. Hugging Face Transformers (huggingface/transformers)
    6. spaCy (explosion/spaCy)
    7. Google Cloud Natural Language AI
    8. AWS Comprehend
    9. ROS 2 (ros2/ros2)
    10. Autoware.Auto (autowarefoundation/autoware.auto)
    11. OpenPilot (commaai/openpilot)
    12. CARLA Simulator (carla-simulator/carla)

    AI recommended 12 alternatives but never named opendilab/LMDrive. 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 opendilab/LMDrive?
    pass
    AI named opendilab/LMDrive explicitly

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

  • If a team adopts opendilab/LMDrive in production, what risks or prerequisites should they evaluate first?
    pass
    AI named opendilab/LMDrive 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 opendilab/LMDrive solve, and who is the primary audience?
    pass
    AI named opendilab/LMDrive explicitly

    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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MARKDOWN (README)
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opendilab/LMDrive — 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