The SMART method can be extended to handle evolving graphs with changing node/edge features or labels by incorporating adaptive mechanisms for feature extraction and reconstruction. One approach could involve dynamically updating the feature extractor based on the evolving characteristics of the graph. This adaptation could involve learning representations that are robust to changes in node/edge features or labels over time. Additionally, the reconstruction process could be enhanced to handle varying feature distributions by incorporating techniques such as domain adaptation or transfer learning. By continuously updating the feature extractor and improving the reconstruction process, SMART can effectively handle evolving graphs with changing node/edge features or labels.