August 22, 2025Open Access

Retrieval-Augmented Generation for Natural Language Processing: A Survey

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This survey reveals advancements in retrieval-augmented generation for large language models, highlighting evaluation and domain expertise issues.

Retrieval-augmented generation enhances large language models by integrating external knowledge databases, addressing major existing limitations.
The paper discusses techniques like retrievers and retrieval fusion, contributing to improved domain-specific expertise in natural language processing.
A comprehensive review of RAG includes discussions on updates, evaluations, and benchmarks alongside various NLP applications and industrial scenarios.
Looking ahead, the paper outlines future directions and challenges facing the development of retrieval-augmented generation technology.

Wu et al. (2025) studied this question.

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This survey reveals advancements in retrieval-augmented generation for large language models, highlighting evaluation and domain expertise issues.