RRepoGEO

REPOGEO REPORT · LITE

locuslab/open-unlearning

Default branch main · commit 4ad738aa · scanned 6/16/2026, 12:02:59 AM

GitHub: 551 stars · 162 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 locuslab/open-unlearning, 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
  • highabout#1
    Refine the About description to emphasize "framework" and "benchmarking"

    Why:

    CURRENT
    [NeurIPS D&B '25] The one-stop repository for LLM unlearning
    COPY-PASTE FIX
    [NeurIPS D&B '25] The unified framework for LLM unlearning benchmarking and evaluation.
  • mediumhomepage#2
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://arxiv.org/abs/2506.12618
  • mediumreadme#3
    Elevate the main README heading to an H1 or H2

    Why:

    CURRENT
    <h3><strong>An easily extensible framework unifying LLM unlearning evaluation benchmarks.</strong></h3>
    COPY-PASTE FIX
    # An Easily Extensible Framework Unifying LLM Unlearning Evaluation Benchmarks

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 locuslab/open-unlearning
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Hugging Face Datasets
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Hugging Face Datasets · recommended 1×
  2. PyTorch · recommended 1×
  3. TensorFlow · recommended 1×
  4. Faker · recommended 1×
  5. ART (Adversarial Robustness Toolbox) by IBM · recommended 1×
  • CATEGORY QUERY
    How can I effectively benchmark and evaluate different LLM unlearning methods for privacy?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Datasets
    2. PyTorch
    3. TensorFlow
    4. Faker
    5. ART (Adversarial Robustness Toolbox) by IBM
    6. Privacy Meter
    7. scikit-learn
    8. Hugging Face Transformers
    9. Hugging Face Evaluate
    10. GLUE/SuperGLUE Benchmarks
    11. EleutherAI's LM Evaluation Harness
    12. PyTorch-Influence-Functions
    13. TensorFlow Privacy
    14. Captum (PyTorch)
    15. SHAP
    16. LIME
    17. Opacus (PyTorch)
    18. Python's `time` module
    19. `nvidia-smi`
    20. `htop`
    21. `top`

    AI recommended 21 alternatives but never named locuslab/open-unlearning. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for a unified framework to research and compare various LLM unlearning techniques and metrics.
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Transformers (huggingface/transformers)
    2. PyTorch (pytorch/pytorch)
    3. TensorFlow (tensorflow/tensorflow)
    4. OpenAI API
    5. Lit-GPT (Lightning-AI/lit-gpt)
    6. DeepSpeed (microsoft/DeepSpeed)
    7. FairScale (facebookresearch/fairscale)
    8. MLflow (mlflow/mlflow)

    AI recommended 8 alternatives but never named locuslab/open-unlearning. 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 locuslab/open-unlearning?
    pass
    AI named locuslab/open-unlearning explicitly

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

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

Embed your GEO score

Drop this badge into the README of locuslab/open-unlearning. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

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MARKDOWN (README)
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HTML
<a href="https://repogeo.com/en/r/locuslab/open-unlearning"><img src="https://repogeo.com/badge/locuslab/open-unlearning.svg" alt="RepoGEO" /></a>
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  • Brand-free category queries5 vs 2 in Lite
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