Reliable and Faithful Generative Explainers for Graph Neural Networks
Graph neural networks (GNNs) have been effectively implemented in a variety of real-world applications, although their underlying work mechanisms remain a mystery.To unveil this mystery and advocate for trustworthy decision-making, many GNN explainers have been proposed.However, existing explainers often face significant challenges, such as the fol