most citedRetrieval Augmented Generation (RAG) and Beyond: A Comprehensive Survey on How to Make your LLMs use External Data More Wisely

13 citations · 13 across the 1 of their papers we have counts for

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1 paper

cs.CL2024★ 13 cited

Retrieval Augmented Generation (RAG) and Beyond: A Comprehensive Survey on How to Make your LLMs use External Data More Wisely

Siyun Zhao, Yuqing Yang, Zilong Wang +3

Large language models (LLMs) augmented with external data have demonstrated remarkable capabilities in completing real-world tasks. Techniques for integrating external data into LL…