Soma Nagy

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2025

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SzegedAI at ArchEHR-QA 2025: Combining LLMs with traditional methods for grounded question answering
Soma Nagy | Bálint Nyerges | Zsombor Kispéter | Gábor Tóth | András Szlúka | Gábor Kőrösi | Zsolt Szántó | Richárd Farkas
Proceedings of the 24th Workshop on Biomedical Language Processing (Shared Tasks)

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.
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