NAACL 2022long8 citations

Learning as Conversation: Dialogue Systems Reinforced for Information Acquisition

Pengshan Cai, Hui Wan, Fei Liu, Mo Yu, Hong Yu, Sachindra Joshi

Abstract

We propose novel AI-empowered chat bots for learning as conversation where a user does not read a passage but gains information and knowledge through conversation with a teacher bot. Our information acquisition-oriented dialogue system employs a novel adaptation of reinforced self-play so that the system can be transferred to various domains without in-domain dialogue data, and can carry out conversations both informative and attentive to users.

BibTeX
@inproceedings{cai-etal-2022-learning,
    title = "Learning as Conversation: Dialogue Systems Reinforced for Information Acquisition",
    author = "Cai, Pengshan  and
      Wan, Hui  and
      Liu, Fei  and
      Yu, Mo  and
      Yu, Hong  and
      Joshi, Sachindra",
    editor = "Carpuat, Marine  and
      de Marneffe, Marie-Catherine  and
      Meza Ruiz, Ivan Vladimir",
    booktitle = "Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies",
    month = jul,
    year = "2022",
    address = "Seattle, United States",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2022.naacl-main.352/",
    doi = "10.18653/v1/2022.naacl-main.352",
    pages = "4781--4796"
}
Learning as Conversation: Dialogue Systems Reinforced for Information Acquisition · NAACL 2022