Geng Tang

Reconstruction Outcomes Look Similar but Processes Differ: Improving Context Consistency and Coverage in Graph Masked Auto-Encoder

Graph Masked Auto-Encoder (GMAE) has emerged as a prevalent self-supervised paradigm, showing superior performance in graph learning. However, existing methods mainly emphasize reconstruction outcomes and give limited specification to how neighborhood context is used for reconstruction. Our experime…