LCR - RAG : Enhancing Logical Consistency in Retrieval-Augmented Generation via Neuro-symbolic Reinforcement Learning
Wenxiang Zheng · Guo Tang · Shixin Jiang · Liangyu Huo · Xiyuan Zhang · Jian Xie · Ming Liu
摘要
Retrieval-Augmented Generation (RAG) is widely used to ground large language models (LLMs) in external knowledge and improve factual accuracy. Prior work has explored iterative and self-reflective mechanisms to refine reasoning, but these approaches rely on internal model judgment and lack formal...