Boosting Conversational Question Answering with Fine-Grained Retrieval-Augmentation and Self-Check

Linhao Ye, Zhikai Lei, Jianghao Yin +3

Retrieval-Augmented Generation (RAG) aims to generate more reliable and accurate responses, by augmenting large language models (LLMs) with the external vast and dynamic knowledge.…