9 citations · 10 across the 7 of their papers we have counts for
Showing 2024Show all
2 papers · 1 filter
cs.CL2024★ 9 cited
RAGChecker: A Fine-grained Framework for Diagnosing Retrieval-Augmented Generation
Dongyu Ru, Lin Qiu, Xiangkun Hu +15
Despite Retrieval-Augmented Generation (RAG) showing promising capability in leveraging external knowledge, a comprehensive evaluation of RAG systems is still challenging due to th…
cs.CL2024
New Desiderata for Direct Preference Optimization
Xiangkun Hu, Tong He, David Wipf
Large language models in the past have typically relied on some form of reinforcement learning with human feedback (RLHF) to better align model responses with human preferences. Ho…