Hai-tao Yu

Towards Adaptive and Retriever-friendly Retrieval-augmented Generation via Reinforcement Learning

ARF-RAG is proposed, an Adaptive Retriever-Friendly Retriever-Friendly Retrieval-Augmented Generation framework that adopts a role-unified mechanism, in which a single LLM simultaneously performs all retrieval-related and generation actions, including retrieval decision-making, query generation, and answer generation, enabling coherent optimization across all components.