@inproceedings{nagy-etal-2025-szegedai,
    title = "{S}zeged{AI} at {A}rch{EHR}-{QA} 2025: Combining {LLM}s with traditional methods for grounded question answering",
    author = {Nagy, Soma  and
      Nyerges, B{\'a}lint  and
      Kisp{\'e}ter, Zsombor  and
      T{\'o}th, G{\'a}bor  and
      Szl{\'u}ka, Andr{\'a}s  and
      K{\H{o}}r{\"o}si, G{\'a}bor  and
      Sz{\'a}nt{\'o}, Zsolt  and
      Farkas, Rich{\'a}rd},
    editor = "Soni, Sarvesh  and
      Demner-Fushman, Dina",
    booktitle = "BioNLP 2025 Shared Tasks",
    month = aug,
    year = "2025",
    address = "Vienna, Austria",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/acl25-workshop-ingestion/2025.bionlp-share.17/",
    pages = "136--149",
    ISBN = "979-8-89176-276-3",
    abstract = "In this paper, we present the SzegedAI team{'}s submissions to the ArchEHR-QA 2025 shared task. Our approaches include multiple prompting techniques for large language models (LLMs), sentence similarity methods, and traditional feature engineering. We are aiming to explore both modern and traditional solutions to the task. To combine the strengths of these diverse methods, we employed different ensembling strategies."
}