Evaluating Post-hoc Explanations for Graph Neural Networks via Robustness Analysis

Neural Information Processing Systems 

This work studies the evaluation of explaining graph neural networks (GNNs), which is crucial to the credibility of post-hoc explainability in practical usage.

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