GHI: Graphormer over Conditioned Hypergraph Incidence for Aspect-Based Sentiment Analysis

In three linesGHI is a Graphormer-based framework for aspect-based sentiment analysis (ABSA). It uses a bipartite hypergraph structure to represent token-hyperedge incidence relations, integrating linguistic and semantic signals. With 247M parameters, GHI outperforms DeBERTa on six SemEval benchmarks and approaches Flan-T5 11B performance on ISE.

Summary generated by Claude — human-verified