98 citations · 107 across the 13 of their papers we have counts for
5 papers · 1 filter
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…
LLMs + Persona-Plug = Personalized LLMs
Jiongnan Liu, Yutao Zhu, Shuting Wang +6
Personalization plays a critical role in numerous language tasks and applications, since users with the same requirements may prefer diverse outputs based on their individual inter…
OmniGen: Unified Image Generation
Shitao Xiao, Yueze Wang, Junjie Zhou +7
The emergence of Large Language Models (LLMs) has unified language generation tasks and revolutionized human-machine interaction. However, in the realm of image generation, a unifi…
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…
RichRAG: Crafting Rich Responses for Multi-faceted Queries in Retrieval-Augmented Generation
Shuting Wang, Xin Yu, Mang Wang +3
Retrieval-augmented generation (RAG) effectively addresses issues of static knowledge and hallucination in large language models. Existing studies mostly focus on question scenario…