2 papers
cs.AI2026
MEGRAG: Multi-Granular Evidence Graphs for Answer-Aware Multi-Hop RAG
Weidong Bao, Yingying Sun, Jun Yang +7
Multi-hop question answering is a fundamental challenge in retrieval-augmented generation (RAG), because deriving an answer requires integrating dispersed evidence. Iterative RAG (…
cs.DB2026
EvoRAG: Making Knowledge Graph-based RAG Automatically Evolve through Feedback-driven Backpropagation
Zhenbo Fu, Yuanzhe Zhang, Qiange Wang +5
Knowledge Graph-based Retrieval-Augmented Generation (KG-RAG) has emerged as a promising paradigm for enhancing LLM reasoning by retrieving multi-hop paths from KGs. However, exist…