RRepoGEO

REPOGEO REPORT · LITE

facebookresearch/vicreg

Default branch main · commit 4e12602f · scanned 5/23/2026, 8:07:39 PM

GitHub: 570 stars · 93 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 facebookresearch/vicreg, 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 specific topics for self-supervised learning and computer vision

    Why:

    COPY-PASTE FIX
    self-supervised-learning, computer-vision, pytorch, representation-learning, deep-learning, unsupervised-learning, image-features
  • mediumabout#2
    Update the repository description for clarity and keywords

    Why:

    CURRENT
    VICReg official code base
    COPY-PASTE FIX
    Official PyTorch implementation of VICReg, a self-supervised learning method for robust visual representation learning from unlabeled image data.
  • lowhomepage#3
    Add the official paper link as the repository homepage

    Why:

    COPY-PASTE FIX
    https://arxiv.org/abs/2105.04906

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 facebookresearch/vicreg
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Lightly
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Lightly · recommended 2×
  2. PyTorch-Image-Models (timm) · recommended 1×
  3. VISSL (Vision Self-Supervised Learning) · recommended 1×
  4. Solo-learn · recommended 1×
  5. PyTorch Lightning Bolts · recommended 1×
  • CATEGORY QUERY
    Seeking a PyTorch library for self-supervised learning to extract powerful image features.
    you: not recommended
    AI recommended (in order):
    1. PyTorch-Image-Models (timm)
    2. Lightly
    3. VISSL (Vision Self-Supervised Learning)
    4. Solo-learn
    5. PyTorch Lightning Bolts

    AI recommended 5 alternatives but never named facebookresearch/vicreg. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Tools for training deep learning models on image data without extensive manual labeling?
    you: not recommended
    AI recommended (in order):
    1. Lightly
    2. DINO / DINOv2
    3. CLIP
    4. SimCLR / SimSiam
    5. PyTorch-Lightning
    6. Label Studio
    7. YOLO

    AI recommended 7 alternatives but never named facebookresearch/vicreg. 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 facebookresearch/vicreg?
    pass
    AI named facebookresearch/vicreg explicitly

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

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

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

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facebookresearch/vicreg — 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