Reachability-Based Formal Verification of Graph Neural Networks with Node and Edge Features

arXiv:2609.30079 · cs.LG, cs.AI · Submitted 2026-09-24 · Read on arXiv

cs.LG, cs.AI

Submitted: 2026-09-24

Updated: 2026-09-24

Code: https://github.com/atumlin/gnnv-saiv26

Project page: https://chrsmrrs.github.io/datasets

Terminology

• Verification — 103× in this paper · explained in 2 episodes
• Robustness — 42× in this paper · explained in 5 episodes
• GNNs — 33× in this paper · explained in 2 episodes
• Benchmark — 25× in this paper · explained in 2 episodes
• Formal Verification — 23× in this paper · explained in 2 episodes
• Aggregation — 17× in this paper · explained in 1 episode
• Power Flow — 12× in this paper
• Abstraction — 9× in this paper · explained in 1 episode
• Adjacency Matrix — 6× in this paper · explained in 1 episode
• Accuracy — 5× in this paper · explained in 1 episode
• Formal Methods — 5× in this paper · explained in 3 episodes
• Adam — 4× in this paper · explained in 2 episodes
• Cascading Failure Analysis — 4× in this paper
• Ablation — 3× in this paper · explained in 1 episode
• International Conference on Learning Representations — 3× in this paper
• Optimal Power Flow — 3× in this paper
• Ablation study — 2× in this paper · explained in 1 episode
• Core — 2× in this paper · explained in 2 episodes
• Graph Convolutional Network — 2× in this paper
• Graph Isomorphism Network with Edge Features — 2× in this paper
• Graph Neural Networks (GNNs) — 2× in this paper · explained in 7 episodes
• Hybrid System — 2× in this paper · explained in 2 episodes
• International Conference on Machine Learning — 2× in this paper
• Representation Learning — 2× in this paper · explained in 2 episodes
• Activation Function — 1× in this paper · explained in 1 episode
• Alignment — 1× in this paper · explained in 1 episode
• Defense Advanced Research Projects Agency — 1× in this paper
• Generalization — 1× in this paper · explained in 13 episodes
• Graph Neural Network (GNN) — 1× in this paper · explained in 3 episodes
• Interpretability — 1× in this paper · explained in 15 episodes
• Loss Function — 1× in this paper · explained in 2 episodes
• National Science Foundation — 1× in this paper
• Structural Constraints — 1× in this paper · explained in 2 episodes
• Transfer Learning — 1× in this paper · explained in 10 episodes

Sources

• The Fifth International Verification of Neural Networks Competition (VNN-COMP 2024): Summary and Results
• The Fourth International Verification of Neural Networks Competition (VNN-COMP 2023): Summary and Results
• Explaining and Harnessing Adversarial Examples
• The 6th International Verification of Neural Networks Competition (VNN-COMP 2025): Summary and Results
• The Third International Verification of Neural Networks Competition (VNN-COMP 2022): Summary and Results

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