@inproceedings{ni-etal-2026-survey,
    title = "A Survey on {LLM}-based Conversational User Simulation",
    author = "Ni, Bo  and
      Wang, Yu  and
      Wang, Leyao  and
      Kveton, Branislav  and
      Dernoncourt, Franck  and
      Xia, Yu  and
      Chen, Hongjie  and
      Luera, Reuben  and
      Basu, Samyadeep  and
      Mukherjee, Subhojyoti  and
      Mathur, Puneet  and
      Ahmed, Nesreen K.  and
      Wu, Junda  and
      Li, Li  and
      Zhang, Huixin  and
      Zhang, Ruiyi  and
      Yu, Tong  and
      Kim, Sungchul  and
      Gu, Jiuxiang  and
      Tu, Zhengzhong  and
      Siu, Alexa  and
      Wang, Zichao  and
      Yoon, Seunghyun  and
      Lipka, Nedim  and
      Park, Namyong  and
      Lin, Zihao  and
      Bui, Trung  and
      Zhao, Yue  and
      Derr, Tyler  and
      Rossi, Ryan A.",
    editor = "Demberg, Vera  and
      Inui, Kentaro  and
      Marquez, Llu{\'i}s",
    booktitle = "Proceedings of the 19th Conference of the {E}uropean Chapter of the {A}ssociation for {C}omputational {L}inguistics (Volume 1: Long Papers)",
    month = mar,
    year = "2026",
    address = "Rabat, Morocco",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-eacl/2026.eacl-long.200/",
    pages = "4266--4301",
    ISBN = "979-8-89176-380-7",
    abstract = "User simulation has long played a vital role in computer science due to its potential to support a wide range of applications. Language, as the primary medium of human communication, forms the foundation of social interaction and behavior. Consequently, simulating conversational behavior has become a key area of study. Recent advancements in large language models (LLMs) have significantly catalyzed progress in this domain by enabling high-fidelity generation of synthetic user conversation. In this paper, we survey recent advancements in LLM-based conversational user simulation. We introduce a novel taxonomy covering user granularity and simulation objectives. Additionally, we systematically analyze core techniques and evaluation methodologies. We aim to keep the research community informed of the latest advancements in conversational user simulation and to further facilitate future research by identifying open challenges and organizing existing work under a unified framework."
}