Meng, Chuan
- Can We Use Large Language Models to Fill Relevance Judgment Holes?
2024/05/09 by Zahra Abbasiantaeb, Chuan Meng, Abbasiantaeb, Zahra +5 · 6 citations
Computer Science · #Computation and Language (cs.CL) #FOS: Computer and information sciences #Information Retrieval (cs.IR) #Natural Language Processing Techniques #Topic Modeling
- RefNet: A Reference-aware Network for Background Based Conversation
2019/08/18 by Chuan Meng, Meng, Chuan, Pengjie Ren +9 · 1 citation
Computer Science · #Topic Modeling #Speech and dialogue systems #Speech Recognition and Synthesis
- Query Performance Prediction using Relevance Judgments Generated by Large Language Models
2024/04/01 by Chuan Meng, Negar Arabzadeh, Meng, Chuan +7 · 2 citations
Decision Sciences · Computer Science · #Data Quality and Management #Web Data Mining and Analysis #Data Management and Algorithms
- Self-seeding and Multi-intent Self-instructing LLMs for Generating Intent-aware Information-Seeking dialogs
2024/02/18 by Arian Askari, Roxana Petcu, Askari, Arian +11 · 2 citations
Computer Science · Business, Management and Accounting · #Semantic Web and Ontologies #Speech and dialogue systems #Business Process Modeling and Analysis
- Conversational Search: From Fundamentals to Frontiers in the LLM Era
2025/06/12 by Mo, Fengran, Meng, Chuan, Aliannejadi, Mohammad +1 · 6 citations
#Computation and Language (cs.CL) #FOS: Computer and information sciences #Information Retrieval (cs.IR)
- UniConv: Unifying Retrieval and Response Generation for Large Language Models in Conversations
2025/07/09 by Mo, Fengran, Gao, Yifan, Meng, Chuan +9 · 6 citations
#Computation and Language (cs.CL) #FOS: Computer and information sciences #Information Retrieval (cs.IR)
- Improving the Reusability of Conversational Search Test Collections
2025/03/12 by Zahra Abbasiantaeb, Abbasiantaeb, Zahra, Chuan Meng +5 · 1 citation
Computer Science · #Expert finding and Q&A systems #FOS: Computer and information sciences #Information Retrieval (cs.IR) #Mobile Crowdsensing and Crowdsourcing #Topic Modeling