4 papers
Prism: Towards Lowering User Cognitive Load in LLMs via Complex Intent Understanding
Zenghua Liao, Jinzhi Liao, Xiang Zhao
Large Language Models are rapidly emerging as web-native interfaces to social platforms. On the social web, users frequently have ambiguous and dynamic goals, making complex intent…
A Question Answering Dataset for Temporal-Sensitive Retrieval-Augmented Generation
Ziyang Chen, Erxue Min, Xiang Zhao +7
We introduce ChronoQA, a large-scale benchmark dataset for Chinese question answering, specifically designed to evaluate temporal reasoning in Retrieval-Augmented Generation (RAG)…
PSSD: Making Large Language Models Self-denial via Human Psyche Structure
Jinzhi Liao, Zenghua Liao, Xiang Zhao
The enhance of accuracy in reasoning results of LLMs arouses the community's interests, wherein pioneering studies investigate post-hoc strategies to rectify potential mistakes. De…
An Adaptive Framework for Generating Systematic Explanatory Answer in Online Q&A Platforms
Ziyang Chen, Xiaobin Wang, Yong Jiang +4
Question Answering (QA) systems face challenges in handling complex questions that require multi-domain knowledge synthesis. The naive RAG models, although effective in information…