8 citations · 13 across the 5 of their papers we have counts for
5 papers
Can LLMs Simulate L2-English Dialogue? An Information-Theoretic Analysis of L1-Dependent Biases
Rena Gao, Xuetong Wu, Tatsuki Kuribayashi +6
This study evaluates Large Language Models' (LLMs) ability to simulate non-native-like English use observed in human second language (L2) learners interfered with by their native f…
A Survey on LLM-based Multi-Agent System: Recent Advances and New Frontiers in Application
Shuaihang Chen, Yuanxing Liu, Wei Han +2
LLM-based Multi-Agent Systems ( LLM-MAS ) have become a research hotspot since the rise of large language models (LLMs). However, with the continuous influx of new related works, t…
Simulation-Free Hierarchical Latent Policy Planning for Proactive Dialogues
Tao He, Lizi Liao, Yixin Cao +5
Recent advancements in proactive dialogues have garnered significant attention, particularly for more complex objectives (e.g. emotion support and persuasion). Unlike traditional t…
Planning Like Human: A Dual-process Framework for Dialogue Planning
Tao He, Lizi Liao, Yixin Cao +4
In proactive dialogue, the challenge lies not just in generating responses but in steering conversations toward predetermined goals, a task where Large Language Models (LLMs) typic…
Conversational Recommender System and Large Language Model Are Made for Each Other in E-commerce Pre-sales Dialogue
Yuanxing Liu, Wei-Nan Zhang, Yifan Chen +6
E-commerce pre-sales dialogue aims to understand and elicit user needs and preferences for the items they are seeking so as to provide appropriate recommendations. Conversational r…