2026
MC-HNN: Learning Latent Structural Semantics and High-Rank Representations for Hypergraph Neural Networks
ICML 2026poster
Hypergraph Neural Networks (HNNs) have emerged as powerful tools for modeling complex high-order correlations. Most existing HNNs adhere to a two-stage message passing paradigm, where node feature propagation is mediated by hyperedges. In this paper, we identify two fundamental theoretical limitatio…