RRepoGEO

REPOGEO REPORT · LITE

thunlp/RCPapers

Default branch master · commit 180fbb57 · scanned 6/10/2026, 6:23:21 PM

GitHub: 889 stars · 167 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
35 /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
3 / 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 thunlp/RCPapers, 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 README's opening statement to emphasize 'curated list'

    Why:

    CURRENT
    ## Must-read papers on Machine Reading Comprehension.
    COPY-PASTE FIX
    ## A Curated List of Must-Read Papers on Machine Reading Comprehension.
  • highlicense#2
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    Create a `LICENSE` file in the repository root. This file should contain the full text of your chosen open-source license (e.g., MIT, Apache-2.0) to clearly state the terms of use for your project.
  • mediumtopics#3
    Expand repository topics and add homepage URL

    Why:

    CURRENT
    paper-list, reading-comprehension
    COPY-PASTE FIX
    Update topics to: `paper-list, reading-comprehension, awesome-list, nlp, machine-learning`. Set the repository's homepage URL in the 'About' section to `https://github.com/thunlp/RCPapers`.

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 thunlp/RCPapers
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Awesome-MRC
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Awesome-MRC · recommended 1×
  2. Papers With Code · recommended 1×
  3. Stanford CS224N · recommended 1×
  4. ACL · recommended 1×
  5. EMNLP · recommended 1×
  • CATEGORY QUERY
    Where can I find a curated list of essential papers on machine reading comprehension?
    you: not recommended
    AI recommended (in order):
    1. Awesome-MRC
    2. Papers With Code
    3. Stanford CS224N
    4. ACL
    5. EMNLP
    6. NAACL
    7. Google Scholar

    AI recommended 7 alternatives but never named thunlp/RCPapers. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the foundational research papers for understanding machine reading comprehension model architectures?
    you: not recommended
    AI recommended (in order):
    1. BiDAF
    2. Transformer
    3. BERT
    4. Attention Mechanism
    5. Memory Networks
    6. Match-LSTM
    7. Pointer Networks
    8. Gated-Attention Reader

    AI recommended 8 alternatives but never named thunlp/RCPapers. 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 thunlp/RCPapers?
    pass
    AI named thunlp/RCPapers explicitly

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

  • If a team adopts thunlp/RCPapers in production, what risks or prerequisites should they evaluate first?
    pass
    AI named thunlp/RCPapers 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 thunlp/RCPapers solve, and who is the primary audience?
    pass
    AI named thunlp/RCPapers explicitly

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

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thunlp/RCPapers — 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