@inproceedings{zhang-etal-2022-persona,
    title = "Persona-Guided Planning for Controlling the Protagonist{'}s Persona in Story Generation",
    author = "Zhang, Zhexin  and
      Wen, Jiaxin  and
      Guan, Jian  and
      Huang, Minlie",
    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://preview.aclanthology.org/fix-sig-urls/2022.naacl-main.245/",
    doi = "10.18653/v1/2022.naacl-main.245",
    pages = "3346--3361",
    abstract = "Endowing the protagonist with a specific personality is essential for writing an engaging story. In this paper, we aim to control the protagonist{'}s persona in story generation, i.e., generating a story from a leading context and a persona description, where the protagonist should exhibit the specified personality through a coherent event sequence. Considering that personas are usually embodied implicitly and sparsely in stories, we propose a planning-based generation model named ConPer to explicitly model the relationship between personas and events. ConPer first plans events of the protagonist{'}s behavior which are motivated by the specified persona through predicting one target sentence, then plans the plot as a sequence of keywords with the guidance of the predicted persona-related events and commonsense knowledge, and finally generates the whole story. Both automatic and manual evaluation results demonstrate that ConPer outperforms state-of-the-art baselines for generating more coherent and persona-controllable stories. Our code is available at \url{https://github.com/thu-coai/ConPer}."
}