RRepoGEO

REPOGEO REPORT · LITE

microsoft/robustlearn

Default branch main · commit 31580cd1 · scanned 6/2/2026, 8:31:50 AM

GitHub: 507 stars · 65 forks

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 microsoft/robustlearn, 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
  • highabout#1
    Refine the 'About' description for better categorization

    Why:

    CURRENT
    Robust machine learning for responsible AI
    COPY-PASTE FIX
    A unified PyTorch library for research on robust machine learning, focusing on adversarial robustness, OOD generalization, and safe transfer learning for responsible AI.
  • mediumreadme#2
    Strengthen the README's opening statement to highlight core focus

    Why:

    CURRENT
    A unified library for research on robust machine learning
    COPY-PASTE FIX
    A unified PyTorch library for cutting-edge research in robust machine learning, encompassing adversarial/backdoor attack and defense, out-of-distribution (OOD) generalization, and safe transfer learning.

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 microsoft/robustlearn
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
CleverHans
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. CleverHans · recommended 1×
  2. Foolbox · recommended 1×
  3. PyTorch-Adversarial-Training-Library · recommended 1×
  4. Albumentations · recommended 1×
  5. Keras ImageDataGenerator · recommended 1×
  • CATEGORY QUERY
    How can I improve machine learning model resilience against adversarial attacks and data shifts?
    you: not recommended
    AI recommended (in order):
    1. CleverHans
    2. Foolbox
    3. PyTorch-Adversarial-Training-Library
    4. Albumentations
    5. Keras ImageDataGenerator
    6. PyTorch's torchvision.transforms
    7. PyTorch
    8. TensorFlow
    9. Scikit-learn
    10. XGBoost
    11. IBM Adversarial Robustness Toolbox (ART)
    12. OpenMax

    AI recommended 12 alternatives but never named microsoft/robustlearn. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What libraries help develop machine learning models that are robust for responsible AI applications?
    you: not recommended
    AI recommended (in order):
    1. IBM AI Fairness 360 (AIF360) (IBM/AIF360)
    2. Microsoft Fairlearn (fairlearn/fairlearn)
    3. Google What-If Tool (WIT) (PAIR-code/what-if-tool)
    4. Google Responsible AI Toolkit (RAIT)
    5. InterpretML (interpretml/interpret)
    6. SHAP (SHapley Additive exPlanations) (shap/shap)
    7. LIME (Local Interpretable Model-agnostic Explanations) (marcotcr/lime)

    AI recommended 7 alternatives but never named microsoft/robustlearn. 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 microsoft/robustlearn?
    pass
    AI named microsoft/robustlearn explicitly

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

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

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

Embed your GEO score

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MARKDOWN (README)
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microsoft/robustlearn — 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