From Phase Transition to Systemic Failure: A Decoupled Analytics Framework for GNN Robustness.

arXiv:2609.31656v1 Announce Type: cross Abstract: Data quality is a major bottleneck for the reliable deployment of graph neural networks (GNNs) in real-world graph mining tasks. Among various sources of degradation, label noise and feature distribution shift