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cs.LG2026
Declarative Explanations for Graph Neural Networks: A Demonstration
Cibo Yu, Haitong Tang, Yinghui Wu +4
Graph Neural Networks (GNNs) have proven effective for graph analytical tasks, yet their "black-box" nature complicates the understanding of their layer-wise behavior and hinders t…
cs.LG2025
SliceGX: Layer-wise GNN Explanation with Model-slicing
Tingting Zhu, Tingyang Chen, Yinghui Wu +2
Ensuring the trustworthiness of graph neural networks (GNNs), which are often treated as black-box models, requires effective explanation techniques. Existing GNN explanations typi…
cs.LG2024★ 17 cited
View-based Explanations for Graph Neural Networks
Tingyang Chen, Dazhuo Qiu, Yinghui Wu +3
Generating explanations for graph neural networks (GNNs) has been studied to understand their behavior in analytical tasks such as graph classification. Existing approaches aim to…