Exact Generalisation Error Exposes Benchmarks Skew Graph Neural Networks Success (or Failure)

ArXi:2509.10337v2 Announce Type: replace-cross Graph Neural Networks (GNNs) have become the standard method for learning from networks across fields ranging from biology to social systems, yet a principled understanding of what enables them to extract meaningful representations, or why performance varies drastically between similar models, remains elusive. These questions can be answered through the generalisation error, which measures the discrepancy between a model's predictions and the true values it is meant to recover.