AI RESEARCH

Invariant-Based Diagnostics for Graph Benchmarks

arXiv CS.LG

ArXi:2605.06462v1 Announce Type: new Progress on graph foundation models is hindered by benchmark practices that conflate the contributions of node features and graph structure, making it hard to tell whether a model actually learns from connectivity, or whether it even needs to. We propose addressing this using graph invariants, i.e., permutation-invariant, task-agnostic structural descriptors that serve as a diagnostic framework for graph benchmarks.