作者位次 #3/6ACL 2026Findings· Findings of ACL
L ingua G ame: A Linguistically Grounded Game-Theoretic Paradigm for Multi-Agent Dialogue Generation
Yuxiao Ye · Yiming Zhang · Yiran Rex Ma · Huiyuan Xie · Huining Zhu · Zhiyuan Liu
摘要
Large Language Models (LLMs) have enabled Multi-Agent Systems (MASs) where agents interact through natural language to solve complex tasks or simulate multi-party dialogues. Recent work on LLM-based MASs has mainly focused on architecture design, such as role assignment and workflow orchestration...