RRepoGEO

REPOGEO REPORT · LITE

bryanswkim/Chain-of-Zoom

Default branch main · commit 5a4f351c · scanned 6/15/2026, 7:43:45 AM

GitHub: 773 stars · 75 forks

AI VISIBILITY SCORE
28 /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
2 / 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 bryanswkim/Chain-of-Zoom, 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 the README's 'Summary' section to explicitly state the project's domain

    Why:

    CURRENT
    Modern single-image super-resolution (SISR) models deliver photo-realistic results at the scale factors on which they are trained, but show notable drawbacks:
    COPY-PASTE FIX
    Chain-of-Zoom is a novel, model-agnostic framework for **extreme image super-resolution**, addressing the limitations of modern SISR models that struggle with magnification beyond their training regime.
  • hightopics#2
    Add relevant topics to the repository

    Why:

    COPY-PASTE FIX
    super-resolution, image-processing, deep-learning, computer-vision, neurips, autoregressive-model, generative-ai, extreme-super-resolution
  • mediumhomepage#3
    Add the project's homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://bryanswkim.github.io/chain-of-zoom/

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 bryanswkim/Chain-of-Zoom
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
NeRFstudio
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. NeRFstudio · recommended 1×
  2. Luma AI · recommended 1×
  3. Instant-NGP · recommended 1×
  4. StyleGAN2/3 · recommended 1×
  5. BigGAN · recommended 1×
  • CATEGORY QUERY
    How to achieve extreme image magnification beyond standard super-resolution model capabilities?
    you: not recommended
    AI recommended (in order):
    1. NeRFstudio
    2. Luma AI
    3. Instant-NGP
    4. StyleGAN2/3
    5. BigGAN
    6. Stable Diffusion
    7. PyTorch
    8. OpenCV
    9. STED Microscopy
    10. PALM/STORM Microscopy
    11. Electron Microscopy (SEM/TEM)

    AI recommended 11 alternatives but never named bryanswkim/Chain-of-Zoom. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are efficient methods for multi-stage image super-resolution without retraining for higher scales?
    you: not recommended
    AI recommended (in order):
    1. Meta-SR
    2. ASR Networks
    3. ESRGAN
    4. Real-ESRGAN
    5. Deep Image Prior (DIP)
    6. SRGAN
    7. SwinIR

    AI recommended 7 alternatives but never named bryanswkim/Chain-of-Zoom. 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 bryanswkim/Chain-of-Zoom?
    pass
    AI named bryanswkim/Chain-of-Zoom explicitly

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

  • If a team adopts bryanswkim/Chain-of-Zoom in production, what risks or prerequisites should they evaluate first?
    pass
    AI named bryanswkim/Chain-of-Zoom 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 bryanswkim/Chain-of-Zoom solve, and who is the primary audience?
    pass
    AI did not name bryanswkim/Chain-of-Zoom — 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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bryanswkim/Chain-of-Zoom — 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