RRepoGEO

REPOGEO REPORT · LITE

nv-tlabs/LION

Default branch main · commit 7711b3d1 · scanned 5/28/2026, 3:48:37 PM

GitHub: 830 stars · 72 forks

AI VISIBILITY SCORE
66 /100
Needs work
Category recall
1 / 2
Avg rank #2.0 when recommended
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 nv-tlabs/LION, 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
    Add a clear, concise introductory sentence to the README

    Why:

    CURRENT
    The README currently starts with a centered title and author list, followed by an 'Update' section, lacking an immediate prose introduction.
    COPY-PASTE FIX
    Insert this sentence immediately after the author/link block and before the 'Update' section: "LION is a research project that introduces Latent Point Diffusion Models for high-quality 3D shape generation, as presented at NeurIPS 2022."
  • highhomepage#2
    Add the project homepage URL to the GitHub 'About' section

    Why:

    COPY-PASTE FIX
    https://nv-tlabs.github.io/LION
  • mediumlicense#3
    Clarify the project's license status in the README

    Why:

    COPY-PASTE FIX
    Add a section to the README, for example, after the 'Install' section: "## License 
 This project is released under the terms specified in the [LICENSE](LICENSE) file. Please refer to the file for full details."

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
1 / 2
50% of queries surface nv-tlabs/LION
Avg rank
#2.0
Lower is better. #1 = top recommendation.
Share of voice
7%
Of all named tools, what % are you?
Top rival
Point-E
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Point-E · recommended 2×
  2. GET3D · recommended 1×
  3. DreamFusion · recommended 1×
  4. Stable-DreamFusion · recommended 1×
  5. Shap-E · recommended 1×
  • CATEGORY QUERY
    Looking for a library to generate diverse 3D shapes using latent diffusion models.
    you: not recommended
    AI recommended (in order):
    1. GET3D
    2. DreamFusion
    3. Stable-DreamFusion
    4. Point-E
    5. Shap-E
    6. Latent-NeRF

    AI recommended 6 alternatives but never named nv-tlabs/LION. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How to synthesize realistic 3D point cloud data with generative AI techniques?
    you: #2
    AI recommended (in order):
    1. Point-E
    2. LION ← you
    3. PointGAN
    4. PC-GAN
    5. PointFlow
    6. Point-VAE
    7. 3D-GAN
    8. GIRAFFE
    9. StyleNeRF
    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 nv-tlabs/LION?
    pass
    AI named nv-tlabs/LION explicitly

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

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

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

Embed your GEO score

Drop this badge into the README of nv-tlabs/LION. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

RepoGEO badge previewLive preview
MARKDOWN (README)
[![RepoGEO](https://repogeo.com/badge/nv-tlabs/LION.svg)](https://repogeo.com/en/r/nv-tlabs/LION)
HTML
<a href="https://repogeo.com/en/r/nv-tlabs/LION"><img src="https://repogeo.com/badge/nv-tlabs/LION.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

nv-tlabs/LION — 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