RRepoGEO

REPOGEO REPORT · LITE

Thinklab-SJTU/awesome-ml4co

Default branch master · commit 391724de · scanned 5/9/2026, 2:57:33 PM

GitHub: 2,115 stars · 241 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 Thinklab-SJTU/awesome-ml4co, 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 README opening to emphasize 'paper list'

    Why:

    CURRENT
    # Awesome Machine Learning for Combinatorial Optimization Resources
We would like to maintain a list of resources that utilize machine learning technologies to solve combinatorial optimization problems.
    COPY-PASTE FIX
    # Awesome Machine Learning for Combinatorial Optimization Papers
This repository is a curated list of research papers and resources that utilize machine learning technologies to solve combinatorial optimization problems.
  • mediumhomepage#2
    Add a homepage URL to the repository settings

    Why:

    COPY-PASTE FIX
    https://github.com/Thinklab-SJTU/awesome-ml4co
  • mediumlicense#3
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    Create a LICENSE file (e.g., MIT or Apache-2.0) in the repository root, or add a clear statement of the applicable license(s) directly in the README if a standard SPDX license is not desired.

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 Thinklab-SJTU/awesome-ml4co
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
google/or-tools
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. google/or-tools · recommended 1×
  2. tensorflow/tensorflow · recommended 1×
  3. pytorch/pytorch · recommended 1×
  4. AlphaZero/MuZero · recommended 1×
  5. DLR-RM/stable-baselines3 · recommended 1×
  • CATEGORY QUERY
    How can machine learning techniques be applied to solve complex combinatorial optimization problems?
    you: not recommended
    AI recommended (in order):
    1. Google OR-Tools (google/or-tools)
    2. TensorFlow (tensorflow/tensorflow)
    3. PyTorch (pytorch/pytorch)
    4. AlphaZero/MuZero
    5. Stable Baselines3 (DLR-RM/stable-baselines3)
    6. Ray RLlib (ray-project/ray)
    7. PyTorch Geometric (pyg-team/pytorch_geometric)
    8. DGL (dmlc/dgl)
    9. DEAP (deap/deap)
    10. PyGAD (ahmedfgad/PyGAD)
    11. MiniZinc (MiniZinc/minizinc-ide)

    AI recommended 11 alternatives but never named Thinklab-SJTU/awesome-ml4co. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Where can I find a comprehensive list of research papers on ML for operations research?
    you: not recommended
    AI recommended (in order):
    1. Google Scholar
    2. arXiv
    3. ResearchGate
    4. Academia.edu
    5. INFORMS PubsOnLine
    6. IEEE Xplore Digital Library
    7. ACM Digital Library
    8. NeurIPS
    9. ICML
    10. ICLR
    11. KDD
    12. AAAI
    13. IJCAI
    14. INFORMS Annual Meeting

    AI recommended 14 alternatives but never named Thinklab-SJTU/awesome-ml4co. 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 Thinklab-SJTU/awesome-ml4co?
    pass
    AI did not name Thinklab-SJTU/awesome-ml4co — 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 Thinklab-SJTU/awesome-ml4co in production, what risks or prerequisites should they evaluate first?
    pass
    AI named Thinklab-SJTU/awesome-ml4co 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 Thinklab-SJTU/awesome-ml4co solve, and who is the primary audience?
    pass
    AI did not name Thinklab-SJTU/awesome-ml4co — 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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Thinklab-SJTU/awesome-ml4co — 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