@inproceedings{saha-etal-2022-proto,
    title = "Proto-Gen: An end-to-end neural generator for persona and knowledge grounded response generation",
    author = "Saha, Sougata  and
      Das, Souvik  and
      Srihari, Rohini",
    editor = "Lim, Heuiseok  and
      Kim, Seungryong  and
      Lee, Yeonsoo  and
      Lin, Steve  and
      Seo, Paul Hongsuck  and
      Suh, Yumin  and
      Jang, Yoonna  and
      Lim, Jungwoo  and
      Hur, Yuna  and
      Son, Suhyune",
    booktitle = "Proceedings of the 1st Workshop on Customized Chat Grounding Persona and Knowledge",
    month = oct,
    year = "2022",
    address = "Gyeongju, Republic of Korea",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2022.ccgpk-1.2",
    pages = "9--14",
    abstract = "In this paper we detail the implementation of Proto-Gen, an end-to-end neural response generator capable of selecting appropriate persona and fact sentences from available options, and generating persona and fact grounded responses. Incorporating a novel interaction layer in an encoder-decoder architecture, Proto-Gen facilitates learning dependencies between facts, persona and the context, and outperforms existing baselines on the FoCus dataset for both the sub-tasks of persona and fact selection, and response generation. We further fine tune Proto-Gen{'}s hyperparameters, and share our results and findings.",
}