RRepoGEO

REPOGEO REPORT · LITE

Jiakui/awesome-bert

Default branch master · commit a1e91d59 · scanned 5/22/2026, 8:23:53 PM

GitHub: 1,844 stars · 347 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
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 Jiakui/awesome-bert, 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 H1 to explicitly state 'Awesome List'

    Why:

    CURRENT
    # This repository is to collect BERT related resources.
    COPY-PASTE FIX
    # Awesome BERT: A Curated List of BERT-related Papers, Applications, and GitHub Resources
  • hightopics#2
    Add 'awesome-list' and 'curated-list' topics

    Why:

    CURRENT
    bert, google-bert, nlp, xlnet
    COPY-PASTE FIX
    bert, google-bert, nlp, xlnet, awesome-list, curated-list, resources
  • highlicense#3
    Add a standard open-source license file

    Why:

    COPY-PASTE FIX
    Create a LICENSE file in the root of the repository with a standard open-source license (e.g., MIT License, Apache-2.0).

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 Jiakui/awesome-bert
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
arXiv.org
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. arXiv.org · recommended 1×
  2. Hugging Face Blog & Documentation · recommended 1×
  3. Papers With Code · recommended 1×
  4. Google AI Blog · recommended 1×
  5. Meta AI Blog · recommended 1×
  • CATEGORY QUERY
    Where can I find comprehensive resources and research papers on large-scale pre-trained language models?
    you: not recommended
    AI recommended (in order):
    1. arXiv.org
    2. Hugging Face Blog & Documentation
    3. Papers With Code
    4. Google AI Blog
    5. Meta AI Blog
    6. Distill.pub
    7. ACL Anthology
    8. EMNLP
    9. NAACL Proceedings
    10. The Gradient
    11. Towards Data Science

    AI recommended 11 alternatives but never named Jiakui/awesome-bert. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the best open-source projects and applications leveraging advanced contextual embeddings for NLP?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Transformers
    2. spaCy
    3. Flair
    4. Sentence-Transformers
    5. Haystack
    6. Gensim
    7. AllenNLP

    AI recommended 7 alternatives but never named Jiakui/awesome-bert. 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 Jiakui/awesome-bert?
    pass
    AI named Jiakui/awesome-bert explicitly

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

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