Optimizing Hypergraph-Based RAG: Toward Better Fact Extraction and Chunk Retrieval
Houda Khrouf, Pedro Fillastre, Sebastiao Correia
cs.AI
Abstract
GraphRAG enables deeper reasoning by structuring knowledge as graphs but struggles with n-ary facts. HyperGraphRAG uses hypergraphs for richer semantics, improving accuracy, yet relies on error-prone LLM extraction and inefficient standard chunk retrieval. We address this by employing self-consistency prompting to improve the extraction, and Personalized PageRank algorithm over hypergraph to enhance chunk retrieval.
Topics
Classified with taxonomy v2 on Sat, 5 Sept 2026.