RRepoGEO

REPOGEO REPORT · LITE

xiaomi-mlab/Orion

Default branch main · commit b08a9ec5 · scanned 6/12/2026, 5:38:38 AM

GitHub: 647 stars · 71 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 xiaomi-mlab/Orion, 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 specific topics to disambiguate the repository

    Why:

    COPY-PASTE FIX
    autonomous-driving, end-to-end-driving, vision-language-models, llm, vlm, causal-reasoning, iccv-2025, deep-learning, pytorch
  • highreadme#2
    Add a concise introductory sentence to the README

    Why:

    CURRENT
    The README currently goes from H1 to author information, then links, then '## Abstract'.
    COPY-PASTE FIX
    Insert the following sentence directly after the H1 and before the author list: 'This repository presents the official code for ORION, a novel framework for end-to-end autonomous driving.'
  • mediumhomepage#3
    Add the project homepage URL

    Why:

    COPY-PASTE FIX
    https://xiaomi-mlab.github.io/Orion/

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 xiaomi-mlab/Orion
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
deepmind/deepmind-research
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. deepmind/deepmind-research · recommended 2×
  2. Waymo Driver · recommended 1×
  3. Cruise Origin · recommended 1×
  4. Tesla Autopilot/FSD · recommended 1×
  5. ApolloAuto/apollo · recommended 1×
  • CATEGORY QUERY
    Need an autonomous driving system that leverages vision-language models for better reasoning.
    you: not recommended
    AI recommended (in order):
    1. Waymo Driver
    2. Cruise Origin
    3. Tesla Autopilot/FSD
    4. Apollo (Baidu) (ApolloAuto/apollo)
    5. CLIP (openai/CLIP)
    6. OWL-ViT (google-research/owlvit)
    7. NVIDIA DriveWorks
    8. Perceiver IO (deepmind/deepmind-research)
    9. Flamingo (deepmind/deepmind-research)
    10. CARLA Simulator (carla-simulator/carla)

    AI recommended 10 alternatives but never named xiaomi-mlab/Orion. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking frameworks to enhance causal reasoning in end-to-end autonomous driving systems.
    you: not recommended
    AI recommended (in order):
    1. CausalNex (causalens/CausalNex)
    2. DoWhy (microsoft/dowhy)
    3. Pyro (pyro-ppl/pyro)
    4. DyNeMo (Dynamic Neural Modeling) (OHBA-analysis/DyNeMo)

    AI recommended 4 alternatives but never named xiaomi-mlab/Orion. 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 xiaomi-mlab/Orion?
    pass
    AI named xiaomi-mlab/Orion explicitly

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

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

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

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xiaomi-mlab/Orion — 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