12 citations · 19 across the 13 of their papers we have counts for
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cs.CL2024★ 1 cited
OmniEval: An Omnidirectional and Automatic RAG Evaluation Benchmark in Financial Domain
Shuting Wang, Jiejun Tan, Zhicheng Dou +1
As a typical and practical application of Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) techniques have gained extensive attention, particularly in vertical do…
cs.IR2024★ 12 cited
HtmlRAG: HTML is Better Than Plain Text for Modeling Retrieved Knowledge in RAG Systems
Jiejun Tan, Zhicheng Dou, Wen Wang +3
Retrieval-Augmented Generation (RAG) has been shown to improve knowledge capabilities and alleviate the hallucination problem of LLMs. The Web is a major source of external knowled…
cs.CL2024★ 4 cited
Small Models, Big Insights: Leveraging Slim Proxy Models To Decide When and What to Retrieve for LLMs
Jiejun Tan, Zhicheng Dou, Yutao Zhu +3
The integration of large language models (LLMs) and search engines represents a significant evolution in knowledge acquisition methodologies. However, determining the knowledge tha…