RRepoGEO

REPOGEO REPORT · LITE

byungsoo-oh/ml-systems-papers

Default branch main · commit b5bdf3ca · scanned 6/16/2026, 10:18:15 PM

GitHub: 622 stars · 45 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 byungsoo-oh/ml-systems-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
    Reposition the README's opening sentence to clarify its curated nature

    Why:

    CURRENT
    Paper list for broad topics in machine learning systems
    COPY-PASTE FIX
    A **curated and organized collection** of essential research papers in machine learning systems, designed to help researchers and engineers quickly find key literature without sifting through generic search results.
  • highlicense#2
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    Create a `LICENSE` file in the repository root with the full text of the Creative Commons Attribution 4.0 International License (CC-BY-4.0). A template can be found at `https://creativecommons.org/licenses/by/4.0/legalcode`.
  • mediumhomepage#3
    Set the repository homepage URL

    Why:

    COPY-PASTE FIX
    https://github.com/byungsoo-oh/ml-systems-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 byungsoo-oh/ml-systems-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. ACM Digital Library · recommended 1×
  4. IEEE Xplore Digital Library · recommended 1×
  5. Microsoft Academic · recommended 1×
  • CATEGORY QUERY
    Where can I find a comprehensive collection of research papers on machine learning systems?
    you: not recommended
    AI recommended (in order):
    1. arXiv.org
    2. Google Scholar
    3. ACM Digital Library
    4. IEEE Xplore Digital Library
    5. Microsoft Academic
    6. Semantic Scholar
    7. MLSys Conference Proceedings

    AI recommended 7 alternatives but never named byungsoo-oh/ml-systems-papers. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking academic papers on optimizing data pipelines and distributed training for machine learning?
    you: not recommended
    AI recommended (in order):
    1. TensorFlow
    2. Horovod
    3. Ray
    4. DeepSpeed
    5. PipeDream
    6. Apache Spark
    7. DALI

    AI recommended 7 alternatives but never named byungsoo-oh/ml-systems-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 byungsoo-oh/ml-systems-papers?
    pass
    AI did not name byungsoo-oh/ml-systems-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 byungsoo-oh/ml-systems-papers in production, what risks or prerequisites should they evaluate first?
    pass
    AI named byungsoo-oh/ml-systems-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 byungsoo-oh/ml-systems-papers solve, and who is the primary audience?
    pass
    AI did not name byungsoo-oh/ml-systems-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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