@inproceedings{teleki-etal-2025-survey,
    title = "A Survey on {LLM}s for Story Generation",
    author = "Teleki, Maria  and
      Bengali, Vedangi  and
      Dong, Xiangjue  and
      Janjur, Sai Tejas  and
      Liu, Haoran  and
      Liu, Tian  and
      Wang, Cong  and
      Liu, Ting  and
      Zhang, Yin  and
      Shipman, Frank  and
      Caverlee, James",
    editor = "Christodoulopoulos, Christos  and
      Chakraborty, Tanmoy  and
      Rose, Carolyn  and
      Peng, Violet",
    booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2025",
    month = nov,
    year = "2025",
    address = "Suzhou, China",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/author-page-yu-wang-polytechnic/2025.findings-emnlp.750/",
    doi = "10.18653/v1/2025.findings-emnlp.750",
    pages = "13954--13966",
    ISBN = "979-8-89176-335-7",
    abstract = "Methods for story generation with Large Language Models (LLMs) have come into the spotlight recently. We create a novel taxonomy of LLMs for story generation consisting of two major paradigms: (i) independent story generation by an LLM, and (ii) author-assistance for story generation {--} a collaborative approach with LLMs supporting human authors. We compare existing works based on their methodology, datasets, generated story types, evaluation methods, and LLM usage. With a comprehensive survey, we identify potential directions for future work"
}