FlexStructRAG: Flexible Structure-Aware Multi-Granular Relational Retrieval for RAG

arXiv:2604.16312v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) systems critically depend on how external knowledge is segmented, structured, and retrieved. Most existing approaches either retrieve fixed-length text chunks, which fragments discourse context, or commit to a single structured index (e.g., a knowledge graph or hypergraph), which hard-codes one relational granularity. This often yields brittle retrieval when queries require different forms of evidence, such as