98 citations · 118 across the 3 of their papers we have counts for
3 papers
cs.IR2024★ 16 cited
Trustworthiness in Retrieval-Augmented Generation Systems: A Survey
Yujia Zhou, Wenbo Zhang, Jingying Shao +10
Retrieval-Augmented Generation (RAG) has quickly grown into a pivotal paradigm in the development of Large Language Models (LLMs). Although existing research mainly emphasizes accu…
cs.CL2024★ 4 cited
DomainRAG: A Chinese Benchmark for Evaluating Domain-specific Retrieval-Augmented Generation
Shuting Wang, Jiongnan Liu, Shiren Song +6
Retrieval-Augmented Generation (RAG) offers a promising solution to address various limitations of Large Language Models (LLMs), such as hallucination and difficulties in keeping u…
cs.CL2023★ 98 cited
Large Language Models for Information Retrieval: A Survey
Yutao Zhu, Huaying Yuan, Shuting Wang +7
As a primary means of information acquisition, information retrieval (IR) systems, such as search engines, have integrated themselves into our daily lives. These systems also serve…