A Survey on RAG Meeting LLMs: Towards Retrieval-Augmented Large Language Models
Hong Kong Polytechnic University · Baidu (China) · +1 more institution
Abstract
As one of the most advanced techniques in AI, Retrieval-Augmented Generation (RAG) can offer reliable and up-to-date external knowledge, providing huge convenience for numerous tasks. Particularly in the era of AI-Generated Content (AIGC), the powerful capacity of retrieval in providing additional knowledge enables RAG to assist existing generative AI in producing high-quality outputs. Recently, Large Language Models (LLMs) have demonstrated revolutionary abilities in language understanding and generation, while still facing inherent limitations such as hallucinations and out-of-date internal knowledge. Given the powerful abilities of RAG in providing the latest and helpful auxiliary information,…
Citation impact
- FWCI
- 163.90
- Percentile
- 100%
- References
- 67
Authors
8Topics & keywords
- Computer science
- Information retrieval
- Natural language processing
- Quality Education