@inproceedings{alies-etal-2025-measuring,
    title = "Measuring Label Ambiguity in Subjective Tasks using Predictive Uncertainty Estimation",
    author = "Alies, Richard  and
      Merdjanovska, Elena  and
      Akbik, Alan",
    editor = "Peng, Siyao  and
      Rehbein, Ines",
    booktitle = "Proceedings of the 19th Linguistic Annotation Workshop (LAW-XIX-2025)",
    month = jul,
    year = "2025",
    address = "Vienna, Austria",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/landing_page/2025.law-1.2/",
    pages = "21--34",
    ISBN = "979-8-89176-262-6",
    abstract = "Human annotations in natural language corpora vary due to differing human perspectives. This is especially prevalent in subjective tasks. In these datasets, certain data samples are more prone to label variation and can be indicated as ambiguous samples."
}