@inproceedings{surya-etal-2023-zero,
    title = "A Zero-Shot Approach for Multi-User Task-Oriented Dialog Generation",
    author = "Surya, Shiv  and
      Jo, Yohan  and
      Biswas, Arijit  and
      Potamianos, Alexandros",
    editor = "Keet, C. Maria  and
      Lee, Hung-Yi  and
      Zarrie{\ss}, Sina",
    booktitle = "Proceedings of the 16th International Natural Language Generation Conference",
    month = sep,
    year = "2023",
    address = "Prague, Czechia",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest_wac_2008/2023.inlg-main.14/",
    doi = "10.18653/v1/2023.inlg-main.14",
    pages = "196--205",
    abstract = "Prior art investigating task-oriented dialog and automatic generation of such dialogs have focused on single-user dialogs between a single user and an agent. However, there is limited study on adapting such AI agents to multi-user conversations (involving multiple users and an agent). Multi-user conversations are richer than single-user conversations containing social banter and collaborative decision making. The most significant challenge impeding such studies is the lack of suitable multi-user task-oriented dialogs with annotations of user belief states and system actions. One potential solution is multi-user dialog generation from single-user data. Many single-user dialogs datasets already contain dialog state information (intents, slots), thus making them suitable candidates. In this work, we propose a novel approach for expanding single-user task-oriented dialogs (e.g. MultiWOZ) to multi-user dialogs in a zero-shot setting."
}