RRepoGEO

REPOGEO REPORT · LITE

chrisliu298/awesome-llm-unlearning

Default branch main · commit e67c9de7 · scanned 6/4/2026, 4:13:10 AM

GitHub: 595 stars · 31 forks

AI VISIBILITY SCORE
22 /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
1 / 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 chrisliu298/awesome-llm-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
  • highreadme#1
    Reposition README opening to emphasize 'awesome list' nature

    Why:

    CURRENT
    A curated collection of papers, surveys, benchmarks, frameworks, and blog posts for machine unlearning in large language models.
    COPY-PASTE FIX
    This is `Awesome LLM Unlearning`, a comprehensive and actively maintained curated collection of papers, surveys, benchmarks, frameworks, and blog posts specifically focused on machine unlearning in large language models. It serves as a central hub for researchers and practitioners to explore the latest advancements and resources in this critical field.
  • highhomepage#2
    Add a homepage URL to the repository's About section

    Why:

    COPY-PASTE FIX
    https://github.com/chrisliu298/awesome-llm-unlearning
  • mediumabout#3
    Clarify the repository description to highlight its 'awesome list' format

    Why:

    CURRENT
    A resource repository for machine unlearning in large language models
    COPY-PASTE FIX
    An awesome list and curated resource repository for machine unlearning in large language models, featuring papers, surveys, benchmarks, and frameworks.

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 chrisliu298/awesome-llm-unlearning
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Hugging Face Transformers
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Hugging Face Transformers · recommended 1×
  2. PyTorch · recommended 1×
  3. TensorFlow · recommended 1×
  4. MEMIT · recommended 1×
  5. ROME · recommended 1×
  • CATEGORY QUERY
    How can I remove specific data or knowledge from large language models for privacy?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Transformers
    2. PyTorch
    3. TensorFlow
    4. MEMIT
    5. ROME
    6. SERAC
    7. Opacus
    8. TensorFlow Privacy
    9. SpaCy
    10. NLTK
    11. Presidio
    12. LangChain
    13. LlamaIndex
    14. Chroma
    15. Pinecone
    16. Weaviate

    AI recommended 16 alternatives but never named chrisliu298/awesome-llm-unlearning. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the best methods for machine unlearning and selective forgetting in AI models?
    you: not recommended
    AI recommended (in order):
    1. SISA (Sharded, Isolated, Sliced, and Aggregated) Training
    2. PyTorch-Influence-Functions
    3. DeltaGrad

    AI recommended 3 alternatives but never named chrisliu298/awesome-llm-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 chrisliu298/awesome-llm-unlearning?
    pass
    AI did not name chrisliu298/awesome-llm-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?

  • If a team adopts chrisliu298/awesome-llm-unlearning in production, what risks or prerequisites should they evaluate first?
    pass
    AI named chrisliu298/awesome-llm-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 chrisliu298/awesome-llm-unlearning solve, and who is the primary audience?
    pass
    AI did not name chrisliu298/awesome-llm-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 chrisliu298/awesome-llm-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
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  • Brand-free category queries5 vs 2 in Lite
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