@inproceedings{razumovskaia-etal-2024-little,
    title = "Little Red Riding Hood Goes around the Globe: Crosslingual Story Planning and Generation with Large Language Models",
    author = "Razumovskaia, Evgeniia  and
      Maynez, Joshua  and
      Louis, Annie  and
      Lapata, Mirella  and
      Narayan, Shashi",
    editor = "Calzolari, Nicoletta  and
      Kan, Min-Yen  and
      Hoste, Veronique  and
      Lenci, Alessandro  and
      Sakti, Sakriani  and
      Xue, Nianwen",
    booktitle = "Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)",
    month = may,
    year = "2024",
    address = "Torino, Italia",
    publisher = "ELRA and ICCL",
    url = "https://aclanthology.org/2024.lrec-main.929",
    pages = "10616--10631",
    abstract = "Previous work has demonstrated the effectiveness of planning for story generation exclusively in a monolingual setting focusing primarily on English. We consider whether planning brings advantages to automatic story generation across languages. We propose a new task of crosslingual story generation with planning and present a new dataset for this task. We conduct a comprehensive study of different plans and generate stories in several languages, by leveraging the creative and reasoning capabilities of large pretrained language models. Our results demonstrate that plans which structure stories into three acts lead to more coherent and interesting narratives, while allowing to explicitly control their content and structure.",
}

Previous work has demonstrated the effectiveness of planning for story generation exclusively in a monolingual setting focusing primarily on English. We consider whether planning brings advantages to automatic story generation across languages. We propose a new task of crosslingual story generation with planning and present a new dataset for this task. We conduct a comprehensive study of different plans and generate stories in several languages, by leveraging the creative and reasoning capabilities of large pretrained language models. Our results demonstrate that plans which structure stories into three acts lead to more coherent and interesting narratives, while allowing to explicitly control their content and structure.
Razumovskaia, Evgeniia Maynez, Joshua Louis, Annie Lapata, Mirella Narayan, Shashi
Little Red Riding Hood Goes around the Globe: Crosslingual Story Planning and Generation with Large Language Models