Ruochang Li

HEAL: Hybrid Enhancement with LLM-based Agents for Text-attributed Hypergraph Self-supervised Representation Learning

This paper studies the problem of text-attributed hypergraph self-supervised representation learning, which aims to generate discriminative representations of hypergraphs without any annotations for downstream tasks. However, real-world hypergraphs could contain incomplete signals, which could deter