@inproceedings{kwon-etal-2023-ground,
    title = "What, When, and How to Ground: Designing User Persona-Aware Conversational Agents for Engaging Dialogue",
    author = "Kwon, Deuksin  and
      Lee, Sunwoo  and
      Kim, Ki Hyun  and
      Lee, Seojin  and
      Kim, Taeyoon  and
      Davis, Eric",
    editor = "Sitaram, Sunayana  and
      Beigman Klebanov, Beata  and
      Williams, Jason D",
    booktitle = "Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 5: Industry Track)",
    month = jul,
    year = "2023",
    address = "Toronto, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2023.acl-industry.68",
    doi = "10.18653/v1/2023.acl-industry.68",
    pages = "707--719",
    abstract = "This paper presents a method for building a personalized open-domain dialogue system to address the WWH (WHAT, WHEN, and HOW) problem for natural response generation in a commercial setting, where personalized dialogue responses are heavily interleaved with casual response turns. The proposed approach involves weighted dataset blending, negative persona information augmentation methods, and the design of personalized conversation datasets to address the challenges of WWH in personalized, open-domain dialogue systems. Our work effectively balances dialogue fluency and tendency to ground, while also introducing a response-type label to improve the controllability and explainability of the grounded responses. The combination of these methods leads to more fluent conversations, as evidenced by subjective human evaluations as well as objective evaluations.",
}

This paper presents a method for building a personalized open-domain dialogue system to address the WWH (WHAT, WHEN, and HOW) problem for natural response generation in a commercial setting, where personalized dialogue responses are heavily interleaved with casual response turns. The proposed approach involves weighted dataset blending, negative persona information augmentation methods, and the design of personalized conversation datasets to address the challenges of WWH in personalized, open-domain dialogue systems. Our work effectively balances dialogue fluency and tendency to ground, while also introducing a response-type label to improve the controllability and explainability of the grounded responses. The combination of these methods leads to more fluent conversations, as evidenced by subjective human evaluations as well as objective evaluations.
Kwon, Deuksin Lee, Sunwoo Kim, Ki Hyun Lee, Seojin Kim, Taeyoon Davis, Eric
What, When, and How to Ground: Designing User Persona-Aware Conversational Agents for Engaging Dialogue