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RAG and RAU: A Survey on Retrieval-Augmented Language Model in Natural Language Processing
May 1, 2024, 4:47 a.m. | Yucheng Hu, Yuxing Lu
cs.CL updates on arXiv.org arxiv.org
Abstract: Large Language Models (LLMs) have catalyzed significant advancements in Natural Language Processing (NLP), yet they encounter challenges such as hallucination and the need for domain-specific knowledge. To mitigate these, recent methodologies have integrated information retrieved from external resources with LLMs, substantially enhancing their performance across NLP tasks. This survey paper addresses the absence of a comprehensive overview on Retrieval-Augmented Language Models (RALMs), both Retrieval-Augmented Generation (RAG) and Retrieval-Augmented Understanding (RAU), providing an in-depth examination of …
arxiv cs.ai cs.cl language language model language processing natural natural language natural language processing processing rag retrieval retrieval-augmented survey type
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