28 citations · 37 across the 14 of their papers we have counts for
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cs.CL2024★ 1 cited
CoFE-RAG: A Comprehensive Full-chain Evaluation Framework for Retrieval-Augmented Generation with Enhanced Data Diversity
Jintao Liu, Ruixue Ding, Linhao Zhang +2
Retrieval-Augmented Generation (RAG) aims to enhance large language models (LLMs) to generate more accurate and reliable answers with the help of the retrieved context from externa…
cs.CL2024★ 1 cited
Let LLMs Take on the Latest Challenges! A Chinese Dynamic Question Answering Benchmark
Zhikun Xu, Yinghui Li, Ruixue Ding +7
How to better evaluate the capabilities of Large Language Models (LLMs) is the focal point and hot topic in current LLMs research. Previous work has noted that due to the extremely…