RRepoGEO

REPOGEO REPORT · LITE

dqxiu/ICL_PaperList

Default branch master · commit 3cd268ab · scanned 6/11/2026, 8:59:31 AM

GitHub: 877 stars · 63 forks

AI VISIBILITY SCORE
17 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 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 dqxiu/ICL_PaperList, 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
  • hightopics#1
    Add relevant topics to the repository

    Why:

    COPY-PASTE FIX
    in-context-learning, icl, paper-list, research-papers, llm, large-language-models, nlp, awesome-list, survey
  • highlicense#2
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    Create a `LICENSE` file in the repository root with the text of the MIT License.
  • mediumhomepage#3
    Add a homepage URL to the repository's 'About' section

    Why:

    COPY-PASTE FIX
    Add a relevant external link (e.g., a project page or related publication) to the repository's homepage field in the 'About' section.

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 dqxiu/ICL_PaperList
Avg rank
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Google Scholar
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Google Scholar · recommended 1×
  2. arXiv.org · recommended 1×
  3. Semantic Scholar · recommended 1×
  4. Papers With Code · recommended 1×
  5. Distill.pub · recommended 1×
  • CATEGORY QUERY
    Where can I find a comprehensive list of research papers on in-context learning?
    you: not recommended
    AI recommended (in order):
    1. Google Scholar
    2. arXiv.org
    3. Semantic Scholar
    4. Papers With Code
    5. Distill.pub
    6. OpenAI
    7. Google AI
    8. DeepMind
    9. GitHub

    AI recommended 9 alternatives but never named dqxiu/ICL_PaperList. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the latest academic resources explaining in-context learning mechanisms and applications?
    you: not recommended
    AI recommended (in order):
    1. In-Context Learning for Large Language Models: A Survey by Dong et al. (2023)
    2. What Can Large Language Models Do in Tree-of-Thought? A Study on Solving Knowledge-Intensive Problems by Yao et al. (2023)
    3. Rethinking the Role of Demonstrations: What Makes In-Context Learning Work? by Min et al. (2022)
    4. Emergent Abilities of Large Language Models by Wei et al. (2022)
    5. In-Context Learning and Induction Heads by Olsson et al. (2022)
    6. A Survey of Large Language Models by Zhao et al. (2023)
    7. Chain-of-Thought Prompting Elicits Reasoning in Large Language Models by Wei et al. (2022)

    AI recommended 7 alternatives but never named dqxiu/ICL_PaperList. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    fail

    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 dqxiu/ICL_PaperList?
    pass
    AI did not name dqxiu/ICL_PaperList — 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 dqxiu/ICL_PaperList in production, what risks or prerequisites should they evaluate first?
    pass
    AI named dqxiu/ICL_PaperList 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 dqxiu/ICL_PaperList solve, and who is the primary audience?
    pass
    AI did not name dqxiu/ICL_PaperList — 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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dqxiu/ICL_PaperList — 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