With the widespread application of graph-structured data in various fields, Graph Neural Networks (GNNs) have attracted significant attention as a powerful tool for analyzing graph data. However, existing GNNs primarily rely on neighborhood node similarity information when learning node representations, overlooking the potential of node differences...