AutoGraph-R1: End-to-End Reinforcement Learning for Knowledge Graph Construction

arXiv:2510.15339v3 Announce Type: cross Abstract: Building effective knowledge graphs (KGs) for Retrieval-Augmented Generation (RAG) is pivotal for advancing question answering (QA) systems. However, its effectiveness is hindered by a fundamental disconnect: the knowledge graph (KG) construction...