3 papers
cs.CL2025
LLM-Driven Preference Data Synthesis for Proactive Prediction of the Next User Utterance in Human-Machine Dialogue
Jinqiang Wang, Huansheng Ning, Jianguo Ding +3
Proactively predicting a users next utterance in human-machine dialogue can streamline interaction and improve user experience. Existing commercial API-based solutions are subject…
cs.CL2025
CTourLLM: Enhancing LLMs with Chinese Tourism Knowledge
Qikai Wei, Mingzhi Yang, Jinqiang Wang +3
Recently, large language models (LLMs) have demonstrated their effectiveness in various natural language processing (NLP) tasks. However, the lack of tourism knowledge limits the p…
cs.CL2025
A Data Synthesis Method Driven by Large Language Models for Proactive Mining of Implicit User Intentions in Tourism
Jinqiang Wang, Huansheng Ning, Tao Zhu +1
In the tourism domain, Large Language Models (LLMs) often struggle to mine implicit user intentions from tourists' ambiguous inquiries and lack the capacity to proactively guide us…