RRepoGEO

REPOGEO REPORT · LITE

graph4ai/graph4nlp

Default branch master · commit c5b6513d · scanned 5/23/2026, 5:26:44 PM

GitHub: 1,688 stars · 207 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
28 /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
2 / 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 graph4ai/graph4nlp, 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
  • hightopics#1
    Add specific GNN-for-NLP topics

    Why:

    CURRENT
    deep-learning, graph-neural-networks, machine-learning, natural-language-processing, nlp, pytorch
    COPY-PASTE FIX
    deep-learning, graph-neural-networks, machine-learning, natural-language-processing, nlp, pytorch, gnn-for-nlp, graph-nlp
  • highhomepage#2
    Populate the Homepage field

    Why:

    COPY-PASTE FIX
    https://dlg4nlp.github.io/index.html
  • mediumreadme#3
    Strengthen README's unique value proposition

    Why:

    CURRENT
    Graph4NLPis an easy-to-use library for R&D at the intersection of **Deep Learning on Graphs** and **Natural Language Processing** (i.e., DLG4NLP).
    COPY-PASTE FIX
    Graph4NLP is the dedicated library for **Deep Learning on Graphs in Natural Language Processing (DLG4NLP)**. It provides an easy-to-use framework specifically designed for researchers and developers to apply Graph Neural Networks directly to NLP tasks, offering specialized modules that differentiate it from general GNN or NLP libraries.

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 graph4ai/graph4nlp
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
PyTorch Geometric (PyG)
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. PyTorch Geometric (PyG) · recommended 2×
  2. Deep Graph Library (DGL) · recommended 2×
  3. Spektral · recommended 2×
  4. Graph Neural Network Library (GNN-Lib) · recommended 2×
  5. Hugging Face Transformers · recommended 1×
  • CATEGORY QUERY
    How can I easily apply graph neural networks to solve natural language processing problems?
    you: not recommended
    AI recommended (in order):
    1. PyTorch Geometric (PyG)
    2. Deep Graph Library (DGL)
    3. Spektral
    4. Graph Neural Network Library (GNN-Lib)
    5. Hugging Face Transformers

    AI recommended 5 alternatives but never named graph4ai/graph4nlp. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What Python libraries simplify building graph neural network models for NLP tasks?
    you: not recommended
    AI recommended (in order):
    1. PyTorch Geometric (PyG)
    2. Deep Graph Library (DGL)
    3. Spektral
    4. Graph Neural Network Library (GNN-Lib)
    5. StellarGraph
    6. PyGSP (PyTorch Geometric Signal Processing)

    AI recommended 6 alternatives but never named graph4ai/graph4nlp. 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 graph4ai/graph4nlp?
    pass
    AI did not name graph4ai/graph4nlp — 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 graph4ai/graph4nlp in production, what risks or prerequisites should they evaluate first?
    pass
    AI named graph4ai/graph4nlp 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 graph4ai/graph4nlp solve, and who is the primary audience?
    pass
    AI named graph4ai/graph4nlp explicitly

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

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