@inproceedings{faye-etal-2025-notmynarrative,
    title = "{N}ot{M}y{N}arrative at {S}em{E}val-2025 Task 10: Do Narrative Features Share Across Languages in Multilingual Encoder Models?",
    author = "Faye, Geraud  and
      Gadek, Guillaume  and
      Ouerdane, Wassila  and
      Hudelot, Celine  and
      Gatepaille, Sylvain",
    editor = "Rosenthal, Sara  and
      Ros{\'a}, Aiala  and
      Ghosh, Debanjan  and
      Zampieri, Marcos",
    booktitle = "Proceedings of the 19th International Workshop on Semantic Evaluation (SemEval-2025)",
    month = jul,
    year = "2025",
    address = "Vienna, Austria",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/corrections-2025-08/2025.semeval-1.10/",
    pages = "58--66",
    ISBN = "979-8-89176-273-2",
    abstract = "Narratives are a new tool to propagate ideas that are sometimes well hidden in press articles. The SemEval-2025 Task 10 focuses on detecting and extracting such narratives in multiple languages. In this paper, we explore the capabilities of encoder-based language models to classify texts according to the narrative they contain. We show that multilingual encoders outperform monolingual models on this dataset, which is challenging due to the small number of samples per class per language. We perform additional experiments to measure the generalization of features in multilingual models to new languages."
}