@inproceedings{razumovskaia-etal-2024-little-red,
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.",
}
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%0 Conference Proceedings
%T Little Red Riding Hood Goes around the Globe: Crosslingual Story Planning and Generation with Large Language Models
%A Razumovskaia, Evgeniia
%A Maynez, Joshua
%A Louis, Annie
%A Lapata, Mirella
%A Narayan, Shashi
%Y Calzolari, Nicoletta
%Y Kan, Min-Yen
%Y Hoste, Veronique
%Y Lenci, Alessandro
%Y Sakti, Sakriani
%Y Xue, Nianwen
%S Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
%D 2024
%8 May
%I ELRA and ICCL
%C Torino, Italia
%F razumovskaia-etal-2024-little-red
%X 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.
%U https://aclanthology.org/2024.lrec-main.929
%P 10616-10631
Markdown (Informal)
[Little Red Riding Hood Goes around the Globe: Crosslingual Story Planning and Generation with Large Language Models](https://aclanthology.org/2024.lrec-main.929) (Razumovskaia et al., LREC-COLING 2024)
ACL