@inproceedings{ronningstad-negi-2025-ltg,
    title = "{LTG} at {S}em{E}val-2025 Task 10: Optimizing Context for Classification of Narrative Roles",
    author = "R{\o}nningstad, Egil  and
      Negi, Gaurav",
    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-1.61/",
    pages = "440--447",
    ISBN = "979-8-89176-273-2",
    abstract = "Our contribution to the SemEval shared task 10, subtask 1 on entity framing, tackles the challenge of providing the necessary segments from longer documents as context for classification with a masked language model. We show how simple entity-oriented heuristics for context selection and the XLM-RoBERTa language model is on par with, or outperforms, Supervised Fine-Tuning with larger generative language models."
}