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Evaluating the effectiveness of biomedical fine-tuning for large language models on clinical tasks
24
Zitationen
10
Autoren
2025
Jahr
Abstract
Fine-tuning LLMs on biomedical data may not yield the anticipated benefits. Alternative approaches, such as retrieval augmentation, should be further explored for effective and reliable clinical integration of LLMs.
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Autoren
Institutionen
- Harvard University(US)
- Humboldt-Universität zu Berlin(DE)
- Massachusetts General Hospital(US)
- Athinoula A. Martinos Center for Biomedical Imaging(US)
- Freie Universität Berlin(DE)
- Charité - Universitätsmedizin Berlin(DE)
- TUM Klinikum(DE)
- Universitätsklinikum Aachen(DE)
- German Cancer Research Center(DE)
- TU Dortmund University(DE)
- Essen University Hospital(DE)
- Cancer Research Center(US)
- Deutschen Konsortium für Translationale Krebsforschung(DE)
- University of California, San Francisco(US)
- Deutsches Herzzentrum München(DE)