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DR-RAG: Applying Dynamic Document Relevance to Retrieval-Augmented Generation for Question-Answering
Autor:
Hei, Zijian, Liu, Weiling, Ou, Wenjie, Qiao, Juyi, Jiao, Junming, Song, Guowen, Tian, Ting, Lin, Yi
Retrieval-Augmented Generation (RAG) has recently demonstrated the performance of Large Language Models (LLMs) in the knowledge-intensive tasks such as Question-Answering (QA). RAG expands the query context by incorporating external knowledge bases t
Externí odkaz:
http://arxiv.org/abs/2406.07348
