RRepoGEO

REPOGEO REPORT · LITE

ict-bigdatalab/awesome-pretrained-models-for-information-retrieval

Default branch main · commit 89968eb0 · scanned 6/3/2026, 2:16:50 AM

GitHub: 676 stars · 49 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 ict-bigdatalab/awesome-pretrained-models-for-information-retrieval, 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
    Clarify the README's opening to emphasize it's an 'awesome list' of papers

    Why:

    CURRENT
    > A curated list of awesome papers related to pre-trained models for information retrieval (a.k.a., **pre-training for IR**). If I missed any papers, feel free to open a PR to include them! And any feedback and contributions are welcome!
    COPY-PASTE FIX
    > This is an **awesome list** – a curated collection of important papers related to pre-trained models for information retrieval (a.k.a., **pre-training for IR**). It is designed for researchers and practitioners to easily discover key research and stay updated. If I missed any papers, feel free to open a PR to include them! And any feedback and contributions are welcome!
  • highlicense#2
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    (Create a LICENSE file in the repository root with a standard open-source license, such as MIT or Apache-2.0, to clarify usage terms.)
  • mediumhomepage#3
    Add a homepage URL to the repository's 'About' section

    Why:

    COPY-PASTE FIX
    (Add a relevant URL to the repository's homepage field in the 'About' section, such as a project page, related research group page, or a link to a hosted version of the list if available.)

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 ict-bigdatalab/awesome-pretrained-models-for-information-retrieval
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. Sentence-BERT (SBERT) · recommended 1×
  3. ColBERT · recommended 1×
  4. DPR - Dense Passage Retriever · recommended 1×
  5. Faiss (Facebook AI Similarity Search) · recommended 1×
  • CATEGORY QUERY
    How to leverage pre-trained language models for better information retrieval systems?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Transformers
    2. Sentence-BERT (SBERT)
    3. ColBERT
    4. DPR - Dense Passage Retriever
    5. Faiss (Facebook AI Similarity Search)
    6. Weaviate
    7. Pinecone
    8. OpenAI GPT-3.5 / GPT-4 API
    9. Google PaLM 2 / Gemini API
    10. Elasticsearch

    AI recommended 10 alternatives but never named ict-bigdatalab/awesome-pretrained-models-for-information-retrieval. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Where can I find research papers on pre-training techniques for dense retrieval in search?
    you: not recommended
    AI recommended (in order):
    1. arXiv
    2. Google Scholar
    3. ACL Anthology
    4. Semantic Scholar
    5. DBLP Computer Science Bibliography
    6. Microsoft Academic
    7. SIGIR
    8. NeurIPS
    9. ICLR
    10. EMNLP
    11. ACL
    12. KDD

    AI recommended 12 alternatives but never named ict-bigdatalab/awesome-pretrained-models-for-information-retrieval. 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 ict-bigdatalab/awesome-pretrained-models-for-information-retrieval?
    pass
    AI did not name ict-bigdatalab/awesome-pretrained-models-for-information-retrieval — 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 ict-bigdatalab/awesome-pretrained-models-for-information-retrieval in production, what risks or prerequisites should they evaluate first?
    pass
    AI named ict-bigdatalab/awesome-pretrained-models-for-information-retrieval 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 ict-bigdatalab/awesome-pretrained-models-for-information-retrieval solve, and who is the primary audience?
    pass
    AI did not name ict-bigdatalab/awesome-pretrained-models-for-information-retrieval — 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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ict-bigdatalab/awesome-pretrained-models-for-information-retrieval — 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