@inproceedings{rosu-etal-2025-archaeology,
    title = "Archaeology at {BEA} 2025 Shared Task: Are Simple Baselines Good Enough?",
    author = "Roșu, Ana  and
      Ispas, Jany-Gabriel  and
      Nisioi, Sergiu",
    editor = {Kochmar, Ekaterina  and
      Alhafni, Bashar  and
      Bexte, Marie  and
      Burstein, Jill  and
      Horbach, Andrea  and
      Laarmann-Quante, Ronja  and
      Tack, Ana{\"i}s  and
      Yaneva, Victoria  and
      Yuan, Zheng},
    booktitle = "Proceedings of the 20th Workshop on Innovative Use of NLP for Building Educational Applications (BEA 2025)",
    month = jul,
    year = "2025",
    address = "Vienna, Austria",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/landing_page/2025.bea-1.98/",
    pages = "1224--1241",
    ISBN = "979-8-89176-270-1",
    abstract = "This paper describes our approach for 5 classification tasks from Building Educational Applications (BEA) 2025 Shared Task.Our methods range from classical machine learning models to large-scale transformers with fine-tuning and prompting strategies. Despite the diversity of approaches, performance differences were often minor, suggesting a strong surface-level signal and the limiting effect of annotation noise{---}particularly around the ``To some extent'' label. Under lenient evaluation, simple models perform competitively, showing their effectiveness in low-resource settings. Our submissions ranked in the top 10 in four of five tracks."
}