REPOGEO REPORT · LITE
acbull/GPT-GNN
Default branch master · commit f26e13c6 · scanned 6/19/2026, 2:23:05 PM
GitHub: 500 stars · 90 forks
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 acbull/GPT-GNN, 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.
- highreadme#1Reposition README opening to clarify it's a research implementation
Why:
CURRENTGPT-GNN is a pre-training framework to initialize GNNs by generative pre-training. It can be applied to large-scale and heterogensous graphs.
COPY-PASTE FIXThis repository provides the official PyTorch implementation for GPT-GNN, a generative pre-training framework for Graph Neural Networks (GNNs) introduced in our KDD 2020 paper, 'Generative Pre-Training of Graph Neural Networks'. GPT-GNN enables initializing GNNs by generative pre-training, applicable to large-scale and heterogeneous graphs.
- highhomepage#2Add a homepage URL to the repository's About section
Why:
COPY-PASTE FIXhttps://dl.acm.org/doi/10.1145/3394486.3403179
- mediumtopics#3Add more specific topics to clarify the repo's nature
Why:
CURRENTgraph-neural-networks, graph-representation-learning, pre-training, self-supervised-learning
COPY-PASTE FIXgraph-neural-networks, graph-representation-learning, pre-training, self-supervised-learning, kdd-2020, official-implementation, generative-models-for-graphs
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.
- DGL (Deep Graph Library) · recommended 1×
- PyG (PyTorch Geometric) · recommended 1×
- Graph Neural Network Benchmark (GNNBench) · recommended 1×
- Graph Data Science Library (GDS) · recommended 1×
- GraphStorm · recommended 1×
- CATEGORY QUERYHow to pre-train graph neural networks effectively on large-scale heterogeneous graph datasets?you: not recommendedAI recommended (in order):
- DGL (Deep Graph Library)
- PyG (PyTorch Geometric)
- Graph Neural Network Benchmark (GNNBench)
- Graph Data Science Library (GDS)
- GraphStorm
- DeepWalk
- Node2Vec
- GraphSAGE
AI recommended 8 alternatives but never named acbull/GPT-GNN. This is the gap to close.
Show full AI answer
- CATEGORY QUERYWhat frameworks support self-supervised pre-training of graph models for various downstream tasks?you: not recommendedAI recommended (in order):
- PyTorch Geometric (PyG)
- Deep Graph Library (DGL)
- Spektral
- GraphGym
- Open Graph Benchmark (OGB)
AI recommended 5 alternatives but never named acbull/GPT-GNN. This is the gap to close.
Show full AI answer
Objective checks
Rule-based audits of metadata signals AI engines weight most.
- Metadata completenesswarn
Suggestion:
- README presencepass
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 acbull/GPT-GNN?passAI named acbull/GPT-GNN explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
- If a team adopts acbull/GPT-GNN in production, what risks or prerequisites should they evaluate first?passAI named acbull/GPT-GNN 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 acbull/GPT-GNN solve, and who is the primary audience?passAI did not name acbull/GPT-GNN — 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
Drop this badge into the README of acbull/GPT-GNN. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.
Live preview[](https://repogeo.com/en/r/acbull/GPT-GNN)<a href="https://repogeo.com/en/r/acbull/GPT-GNN"><img src="https://repogeo.com/badge/acbull/GPT-GNN.svg" alt="RepoGEO" /></a>Subscribe to Pro for deep diagnoses
acbull/GPT-GNN — 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