@inproceedings{yu-etal-2025-multi,
    title = "Multi-Agent Based Character Simulation for Story Writing",
    author = "Yu, Tian  and
      Shi, Ken  and
      Zhao, Zixin  and
      Penn, Gerald",
    editor = "Padmakumar, Vishakh  and
      Gero, Katy  and
      Wambsganss, Thiemo  and
      Sterman, Sarah  and
      Huang, Ting-Hao  and
      Zhou, David  and
      Chung, John",
    booktitle = "Proceedings of the Fourth Workshop on Intelligent and Interactive Writing Assistants (In2Writing 2025)",
    month = may,
    year = "2025",
    address = "Albuquerque, New Mexico, US",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/moar-dois/2025.in2writing-1.9/",
    doi = "10.18653/v1/2025.in2writing-1.9",
    pages = "87--108",
    ISBN = "979-8-89176-239-8",
    abstract = "This work proposes a novel multi-agent story-generation system that writes stories from a narrative plan. Traditional approaches tend to generate a section of text directly from its outline. Our system, by contrast, divides this elaboration process into role-play and rewrite steps, where the former step enacts the story in chronological order with LLM-backed character agents, and the latter step refines the role-play result to align with a narrative plan. We show that the stories produced by our system are preferable to two other LLM-based story-generation approaches. We attribute this advancement to the benefits of incorporating a character-based simulation strategy."
}