@inproceedings{hosseinzadeh-etal-2025-xlm,
    title = "{XLM}-Muriel at {S}em{E}val-2025 Task 11: Hard Parameter Sharing for Multi-lingual Multi-label Emotion Detection",
    author = "Hosseinzadeh, Pouya  and
      Ebadzadeh, Mohammad Mehdi  and
      Zeinali, Hossein",
    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-1.45/",
    pages = "314--318",
    ISBN = "979-8-89176-273-2",
    abstract = "Throughout this paper we present our system developed to solve SemEval-2025 Task 11: Bridging the Gap in Text-based Emotion Detection Track A. To participate in this contest, we use an architecture based on a pretrained encoder model as the shared part of the model and then add specific head to adapt the shared part for each language. In the first part of this report, we will introduce the task and the specific track in which we participated and then elaborate on the dataset and the system we developed to handle the task. Finally, we will analyze our results and discuss limitations and potential strength point of our solution that could be leveraged in future work to improve results on similar tasks."
}