RRepoGEO

REPOGEO REPORT · LITE

chaiyujin/glow-pytorch

Default branch master · commit 487a6b14 · scanned 5/31/2026, 10:18:04 PM

GitHub: 514 stars · 80 forks

AI VISIBILITY SCORE
22 /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
1 / 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 chaiyujin/glow-pytorch, 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
    Reposition README's opening to highlight PyTorch Glow for image generation and manipulation

    Why:

    CURRENT
    # Glow
This is pytorch implementation of paper "Glow: Generative Flow with Invertible 1x1 Convolutions".
    COPY-PASTE FIX
    # Glow: PyTorch Implementation for High-Quality Image Generation and Manipulation
This repository offers a robust PyTorch implementation of OpenAI's "Glow: Generative Flow with Invertible 1x1 Convolutions" paper, designed for researchers and practitioners working with generative models.
  • mediumtopics#2
    Add more specific topics to improve category matching

    Why:

    CURRENT
    flow, generative, glow, pytorch
    COPY-PASTE FIX
    flow, generative, glow, pytorch, invertible-neural-networks, image-generation, image-manipulation, density-estimation
  • lowhomepage#3
    Add a homepage URL to the repository metadata

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    https://github.com/chaiyujin/glow-pytorch

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 chaiyujin/glow-pytorch
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
NICE
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. NICE · recommended 1×
  2. RealNVP · recommended 1×
  3. Glow · recommended 1×
  4. Variational Diffusion Models · recommended 1×
  5. Denoising Diffusion Probabilistic Models · recommended 1×
  • CATEGORY QUERY
    I need a PyTorch implementation for generative flow models to create high-quality images.
    you: not recommended
    AI recommended (in order):
    1. NICE
    2. RealNVP
    3. Glow
    4. Variational Diffusion Models
    5. Denoising Diffusion Probabilistic Models
    6. DDPM
    7. Improved DDPM
    8. StyleGAN
    9. StyleGAN2
    10. StyleGAN3
    11. FFJORD

    AI recommended 11 alternatives but never named chaiyujin/glow-pytorch. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking PyTorch tools for invertible neural networks to perform image generation and manipulation.
    you: not recommended
    AI recommended (in order):
    1. FrEIA
    2. NICE / RealNVP / GLOW implementations
    3. Invertible Residual Networks (i-ResNet) implementations
    4. TorchFlow
    5. PyTorch Geometric

    AI recommended 5 alternatives but never named chaiyujin/glow-pytorch. 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 chaiyujin/glow-pytorch?
    pass
    AI did not name chaiyujin/glow-pytorch — 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?

  • If a team adopts chaiyujin/glow-pytorch in production, what risks or prerequisites should they evaluate first?
    pass
    AI named chaiyujin/glow-pytorch 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 chaiyujin/glow-pytorch solve, and who is the primary audience?
    pass
    AI did not name chaiyujin/glow-pytorch — 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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chaiyujin/glow-pytorch — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

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  • Brand-free category queries5 vs 2 in Lite
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