RRepoGEO

REPOGEO REPORT · LITE

Cartus/Automated-Fact-Checking-Resources

Default branch main · commit c754fb1f · scanned 6/5/2026, 12:13:25 AM

GitHub: 570 stars · 63 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 Cartus/Automated-Fact-Checking-Resources, 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 core purpose statement in the README's opening

    Why:

    COPY-PASTE FIX
    # Automated Fact-Checking Resources

This repository serves as a continuously updated, curated collection of relevant resources, including papers and datasets, from our survey A Survey on Automated Fact-Checking (TACL 2022) and Multimodal Automated Fact-Checking: A Survey (EMNLP 2023). It unifies various components and definitions into a common framework for researchers and practitioners in automated fact-checking (AFC) across text and other modalities.
  • mediumabout#2
    Add a homepage URL to the repository's About section

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    https://aclanthology.org/2022.tacl-1.1/
  • lowabout#3
    Refine the repository's About description for clarity and unique value

    Why:

    CURRENT
    Links to conference/journal publications in automated fact-checking (resources for the TACL22/EMNLP23 paper).
    COPY-PASTE FIX
    A continuously updated, curated collection of key conference and journal publications, datasets, and resources for automated fact-checking, serving as a living companion to our TACL 2022 and EMNLP 2023 survey papers.

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 Cartus/Automated-Fact-Checking-Resources
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
ACL Anthology
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. ACL Anthology · recommended 1×
  2. arXiv · recommended 1×
  3. Google Scholar · recommended 1×
  4. ACM Digital Library · recommended 1×
  5. IEEE Xplore · recommended 1×
  • CATEGORY QUERY
    Where can I find a comprehensive survey of recent research in automated fact-checking?
    you: not recommended
    AI recommended (in order):
    1. ACL Anthology
    2. arXiv
    3. Google Scholar
    4. ACM Digital Library
    5. IEEE Xplore
    6. Frontiers in Artificial Intelligence
    7. Information Processing & Management
    8. Journal of the Association for Information Science and Technology
    9. Semantic Scholar
    10. EMNLP
    11. ACL
    12. NAACL
    13. AAAI
    14. IJCAI
    15. KDD

    AI recommended 15 alternatives but never named Cartus/Automated-Fact-Checking-Resources. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the leading academic papers on claim detection and rumor identification for NLP?
    you: not recommended
    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 Cartus/Automated-Fact-Checking-Resources?
    pass
    AI did not name Cartus/Automated-Fact-Checking-Resources — 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 Cartus/Automated-Fact-Checking-Resources in production, what risks or prerequisites should they evaluate first?
    pass
    AI named Cartus/Automated-Fact-Checking-Resources 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 Cartus/Automated-Fact-Checking-Resources solve, and who is the primary audience?
    pass
    AI did not name Cartus/Automated-Fact-Checking-Resources — 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

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Cartus/Automated-Fact-Checking-Resources — 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