Writing persuasive arguments is a challenging task for both humans and machines. It entails incorporating high-level beliefs from various perspectives on the topic, along with deliberate reasoning and planning to construct a coherent narrative. Current language models often generate surface tokens autoregressively, lacking explicit integration of these underlying controls, resulting in limited output diversity and coherence. In this work, we propose a persona-based multi-agent framework for argument writing. Inspired by the human debate, we first assign each agent a persona representing its high-level beliefs from a unique perspective, and then design an agent interaction process so that the agents can collaboratively debate and discuss the idea to form an overall plan for argument writing. Such debate process enables fluid and nonlinear development of ideas. We evaluate our framework on argumentative essay writing. The results show that our framework can generate more diverse and persuasive arguments through both automatic and human evaluations.
Beyond Symmetric Agents: Cognitive Diversity and Multi-Agent Debate in Small Language Models
Boston Children’s Hospital, Harvard Medical School（波士顿儿童医院，哈佛医学院）；Harvard School of Engineering and Applied Sciences, Harvard College（哈佛工程与应用科学学院，哈佛学院）
CWF: A Collaborative Writing Framework for Personalized and Reliable Popular Science Writing
Huazhong University of Science and Technology（华中科技大学）；Philosophy and Social Sciences Laboratory of Big Data and National Communication Strategy, Ministry of Education（大数据与国家传播战略教育部哲学社会科学实验室）；The National Key Laboratory of Multispectral Information Intelligent Processing Technology（多谱信息智能处理技术全国重点实验室）
Multi-Persona Debate System for Automated Scientific Hypothesis Generation
Department of Materials Science & Engineering, Ajou University（材料科学与工程系，阿乔大学）；Department of Energy Systems Research, Ajou University（能源系统研究系，阿乔大学）；Department of Nuclear Science and Engineering, Massachusetts Institute of Technology（核科学与工程系，麻省理工学院）；Department of Materials Science and Engineering, Massachusetts Institute of Technology（材料科学与工程系，麻省理工学院）；Department of Materials Science and Engineering, Ulsan National Institute of Science and Technology（材料科学与工程系，乌山国家科学与技术研究院）；Graduate School of Artificial Intelligence, Ulsan National Institute of Science and Technology（人工智能研究生院，乌山国家科学与技术研究院）
AI Debaters are More Persuasive when Arguing in Alignment with Their Own Beliefs
FAIR, IALAB, Universidad de Buenos Aires（FAIR、IALAB、布宜诺斯艾利斯大学）；Universidad de Buenos Aires（布宜诺斯艾利斯大学）；Universidad Nacional de Córdoba（科尔多瓦国立大学）；BAISH, Universidad de Buenos Aires（BAISH、布宜诺斯艾利斯大学）；Instituto de Investigación en Informática LIDI, Universidad Nacional de La Plata（信息研究所LIDI、拉普拉塔国立大学；CONICET）；CONICET（计算机科学与工程系，南大学及ICIC UNS-CONICET）；Dept. of Comp. Sci. and Eng., Universidad Nacional del Sur & ICIC UNS-CONICET（人工智能研究所（IIIA-CSIC），西班牙）；Artificial Intelligence Research Institute (IIIA-CSIC), ES
University of California, Los Angeles（加州大学洛杉矶分校）；Seoul National University（首尔国立大学）；Qatar Computing Research Institute（卡塔尔计算研究所）；Google（谷歌）；George Washington University（乔治华盛顿大学）；Stanford University（斯坦福大学）；Scale AI；University of Washington（华盛顿大学）
