2024

• Bäumer, F.S., Schultenkämper, S., Geierhos, M., & Lee, Y. S. (2024): Mirroring Privacy Risks with Digital Twins: When Pieces of Personal Data Suddenly Fit Together. SN Computer Science. In Press.
• Damm, H., Pakull, T.M.G., Eryılmaz, B., Becker, H., Idrissi-Yaghir, A., Schäfer, H., Schultenkämper, S., & Friedrich, C.M. (2024). WisPerMed at “Discharge Me!”: Advancing Text Generation in Healthcare with Large Language Models, Dynamic Expert Selection, and Priming Techniques on MIMIC-IV. In: Demner-Fushman, D., Ananiadou, S., Miwa, M., Roberts, K., Tsujii, J. (eds) Proceedings of the 23rd Workshop on Biomedical Natural Language Processing, pp. 105–121. Association for Computational Linguistics, Stroudsburg, PA, USA.
• Bäumer, F., Brandt-Pook, H., Matutat, A., Maoro, F., Pelkmann, D., & Schultenkämper, S. (2024). Lektionen und Anwendungsfälle aus der Implementierung von Retrieval-Augmented-Generation-Systemen. M. Klein, D. Krupka, C. Winter, M. Gergeleit, L. Martin, & Gesellschaft für Informatik e.V. (GI) (Eds.), INFORMATIK 2024 (Vol. 352). Berlin: Köllen Druck+Verlag GmbH.
• Schultenkämper, S., Bäumer, F.S. (2024): Pixels versus Privacy: Leveraging Vision-Language Models for Sensitive Information Extraction. International Journal on Advances in Security 17. IARIA Journals.
• Schultenkämper, S., Bäumer, F.S. (2024): Structured Knowledge Extraction for Digital Twins: Leveraging LLMs to Analyze Tweets. 24th International Conference on Innovations for Community Services. In: Phillipson, F., Eichler, G., Erfurth, C., Fahrnberger, G. (eds) Innovations for Community Services. I4CS 2024. Communications in Computer and Information Science, vol 2109. Springer, Cham.
• Maoro, F., & Geierhos, M. (2024). Vertrauenswürdige Künstliche Intelligenz für polizeiliche Anwendungen. In Kongress KI@HSBI2023 – Solutions im Fokus – Posterbeiträge (Nr. 1/2024). Schriftenreihe des Institute for Data Science Solutions. DOI: 10.60802/sidas.2024.1