RRepoGEO

REPOGEO REPORT · LITE

TSCenter/awesome-time-series-papers

Default branch master · commit 2df4d43b · scanned 6/7/2026, 1:18:17 AM

GitHub: 1,012 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 TSCenter/awesome-time-series-papers, 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 to differentiate from academic platforms

    Why:

    CURRENT
    This is an awesome list of the latest time series papers and code from top AI venues!
    COPY-PASTE FIX
    This GitHub repository is a human-curated awesome list, providing a categorized collection of the latest time series papers and code from top AI venues. It offers a focused alternative to broad academic search engines or conference proceedings.
  • mediumabout#2
    Refine the 'About' description to emphasize curation and GitHub hosting

    Why:

    CURRENT
    An Awesome List of the latest time series papers and code from top AI venues.
    COPY-PASTE FIX
    A human-curated GitHub awesome list of the latest time series papers and code from top AI venues, categorized for easy discovery.
  • lowhomepage#3
    Add the repository URL as the homepage

    Why:

    COPY-PASTE FIX
    https://github.com/TSCenter/awesome-time-series-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 TSCenter/awesome-time-series-papers
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. Google Scholar · recommended 1×
  3. NeurIPS (Conference on Neural Information Processing Systems) · recommended 1×
  4. ICML (International Conference on Machine Learning) · recommended 1×
  5. KDD (ACM SIGKDD Conference on Knowledge Discovery and Data Mining) · recommended 1×
  • CATEGORY QUERY
    Where can I find recent research papers on advanced time series analysis techniques?
    you: not recommended
    AI recommended (in order):
    1. arXiv.org
    2. Google Scholar
    3. NeurIPS (Conference on Neural Information Processing Systems)
    4. ICML (International Conference on Machine Learning)
    5. KDD (ACM SIGKDD Conference on Knowledge Discovery and Data Mining)
    6. Journal of Machine Learning Research (JMLR)
    7. The American Economic Review (AER)
    8. Journal of Econometrics

    AI recommended 8 alternatives but never named TSCenter/awesome-time-series-papers. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the latest academic resources for time series forecasting and anomaly detection?
    you: not recommended
    AI recommended (in order):
    1. NeurIPS
    2. ICML
    3. KDD
    4. AAAI
    5. The Journal of Machine Learning Research
    6. IEEE Transactions on Knowledge and Data Engineering
    7. International Journal of Forecasting

    AI recommended 7 alternatives but never named TSCenter/awesome-time-series-papers. 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 TSCenter/awesome-time-series-papers?
    pass
    AI did not name TSCenter/awesome-time-series-papers — 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 TSCenter/awesome-time-series-papers in production, what risks or prerequisites should they evaluate first?
    pass
    AI named TSCenter/awesome-time-series-papers 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 TSCenter/awesome-time-series-papers solve, and who is the primary audience?
    pass
    AI did not name TSCenter/awesome-time-series-papers — 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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TSCenter/awesome-time-series-papers — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

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  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite