RRepoGEO

REPOGEO REPORT · LITE

openai/glow

Default branch master · commit 91b2c577 · scanned 5/12/2026, 11:37:55 AM

GitHub: 3,183 stars · 525 forks

AI VISIBILITY SCORE
71 /100
Needs work
Category recall
1 / 2
Avg rank #2.0 when recommended
Rule findings
2 pass · 0 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 openai/glow, 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 'tensorflow' to repository topics

    Why:

    CURRENT
    paper
    COPY-PASTE FIX
    paper, tensorflow
  • mediumreadme#2
    Clarify TensorFlow usage in README's opening

    Why:

    CURRENT
    Code for reproducing results in "Glow: Generative Flow with Invertible 1x1 Convolutions"
    COPY-PASTE FIX
    This repository provides TensorFlow code for reproducing results in "Glow: Generative Flow with Invertible 1x1 Convolutions", a generative flow model for high-quality image synthesis.
  • lowtopics#3
    Add more specific generative model topics

    Why:

    CURRENT
    paper, tensorflow
    COPY-PASTE FIX
    paper, tensorflow, generative-models, normalizing-flows, image-synthesis

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 openai/glow
Avg rank
#2.0
Lower is better. #1 = top recommendation.
Share of voice
10%
Of all named tools, what % are you?
Top rival
NICE / RealNVP
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. NICE / RealNVP · recommended 1×
  2. i-ResNet · recommended 1×
  3. FrEIA · recommended 1×
  4. PyTorch Flow · recommended 1×
  5. TensorFlow Generative Adversarial Networks (GANs) · recommended 1×
  • CATEGORY QUERY
    How can I generate high-quality images using invertible neural networks?
    you: #2
    AI recommended (in order):
    1. NICE / RealNVP
    2. Glow ← you
    3. i-ResNet
    4. FrEIA
    5. PyTorch Flow
    Show full AI answer
  • CATEGORY QUERY
    What generative models are available for image synthesis using TensorFlow?
    you: not recommended
    AI recommended (in order):
    1. TensorFlow Generative Adversarial Networks (GANs)
    2. TensorFlow Hub (TF-Hub)
    3. TensorFlow.js (tensorflow/tfjs)
    4. TensorFlow Probability (tensorflow/probability)
    5. Keras-GAN (eriklindernoren/Keras-GAN)

    AI recommended 5 alternatives but never named openai/glow. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    pass

  • 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 openai/glow?
    pass
    AI named openai/glow explicitly

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

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

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

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