arxiv Preprint - Understanding Retrieval Augmentation for Long-Form Question Answering

In this episode we discuss Understanding Retrieval Augmentation for Long-Form Question Answering by Hung-Ting Chen, Fangyuan Xu, Shane A. Arora, Eunsol Choi. This paper examines the impact of retrieval-augmented language models on long-form question answering. The authors compare the generated answers using the same evidence documents to analyze how retrieval augmentation affects different language models. They also investigate the quality of the retrieval document set and its effect on the generated answers.