U niversal RAG : Retrieval-Augmented Generation over Corpora of Diverse Modalities and Granularities
Woongyeong Yeo · Kangsan Kim · Soyeong Jeong · Jinheon Baek · Sung Ju Hwang
摘要
Retrieval-Augmented Generation (RAG) has shown substantial promise in improving factual accuracy by grounding model responses with external knowledge relevant to queries. However, most existing approaches are limited to a text-only corpus, and while recent efforts have extended RAG to other modal...