A new framework classifies message-passing link representation models by neighborhood radius and base expressiveness, yielding a hierarchy in which SEAL is most expressive, plus a synthetic benchmark and symmetry-based practical guidance.
How symmetric are real-world graphs? a large-scale study
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Bridging Theory and Practice in Link Representation with Graph Neural Networks
A new framework classifies message-passing link representation models by neighborhood radius and base expressiveness, yielding a hierarchy in which SEAL is most expressive, plus a synthetic benchmark and symmetry-based practical guidance.