Temporal Generalization Estimation in Evolving Graphs: Overcoming Representation Distortion through Self-Supervised Learning

The core message of this article is that representation distortion is unavoidable as graph neural networks (GNNs) are deployed on evolving graphs, and proposes a self-supervised method called SMART to effectively estimate the temporal generalization performance of GNNs without human annotation after deployment.