RRepoGEO

REPOGEO REPORT · LITE

pfnet-research/sngan_projection

Default branch master · commit e84b1a5f · scanned 6/30/2026, 8:53:06 PM

GitHub: 1,103 stars · 201 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

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 pfnet-research/sngan_projection, 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

2 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • mediumhomepage#1
    Set the repository homepage URL

    Why:

    COPY-PASTE FIX
    https://openreview.net/forum?id=B1QRgziT-
  • mediumreadme#2
    Clarify the existing license in the README

    Why:

    COPY-PASTE FIX
    Add the following line to your README, ideally near the top or in a dedicated section: 'This project is licensed under the terms found in the [LICENSE](LICENSE) file.'

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 pfnet-research/sngan_projection
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
StyleGAN3
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. StyleGAN3 · recommended 1×
  2. StyleGAN2-ADA · recommended 1×
  3. BigGAN · recommended 1×
  4. Diff-GAN · recommended 1×
  5. ContraGAN · recommended 1×
  • CATEGORY QUERY
    How to generate high-quality images conditional on specific categories using advanced GAN architectures?
    you: not recommended
    AI recommended (in order):
    1. StyleGAN3
    2. StyleGAN2-ADA
    3. BigGAN
    4. Diff-GAN
    5. ContraGAN
    6. SAGAN
    7. AC-GAN

    AI recommended 7 alternatives but never named pfnet-research/sngan_projection. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a deep learning library for stable conditional image synthesis with spectral normalization.
    you: not recommended
    AI recommended (in order):
    1. PyTorch
    2. TensorFlow
    3. JAX
    4. Keras
    5. MXNet

    AI recommended 5 alternatives but never named pfnet-research/sngan_projection. 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 pfnet-research/sngan_projection?
    pass
    AI named pfnet-research/sngan_projection explicitly

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

  • If a team adopts pfnet-research/sngan_projection in production, what risks or prerequisites should they evaluate first?
    pass
    AI named pfnet-research/sngan_projection 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 pfnet-research/sngan_projection solve, and who is the primary audience?
    pass
    AI named pfnet-research/sngan_projection 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 pfnet-research/sngan_projection. 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/pfnet-research/sngan_projection.svg)](https://repogeo.com/en/r/pfnet-research/sngan_projection)
HTML
<a href="https://repogeo.com/en/r/pfnet-research/sngan_projection"><img src="https://repogeo.com/badge/pfnet-research/sngan_projection.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

pfnet-research/sngan_projection — 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
pfnet-research/sngan_projection — RepoGEO report