2024

  • Bäumer, F. S., Brandt-Pook, H., Matutat, A., Maoro, F., Pelkmann, D., & Schultenkämper, S. (2024). Lektionen und Anwendungsfälle aus der Implementierung von Retrieval-Augmented-Generation-Systemen. In 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. https://doi.org/10.18420/inf2024_146
  • 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, 5(8). https://doi.org/10.1007/s42979-024-03413-z
  • 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 D. Demner-Fushman, S. Ananiadou, M. Miwa, K. Roberts, & J. Tsujii (Eds.), Proceedings of the 23rd Workshop on Biomedical Natural Language Processing (pp. 105–121). Stroudsburg, PA, USA: Association for Computational Linguistics. https://doi.org/10.18653/v1/2024.bionlp-1.9
  • Kant, G., Zhelyazkov, I., Thielmann, A., Weisser, C., Schlee, M., Ehrling, C., Säfken, B., & Kneib, T. (2024). One-Way Ticket to the Moon? An NLP-Based Insight on the Phenomenon of Small-Scale Neo-Broker Trading. Social Network Analysis and Mining, 14(1), Article 121. https://doi.org/10.1007/s13278-024-01273-2
  • 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. https://doi.org/10.60802/sidas.2024.1
  • Reuter, A., Khadka, B., Thielmann, A., Weisser, C., Fischer, S., & Säfken, B. (2024). GPTopic: Dynamic and Interactive Topic Representations. arXiv. https://arxiv.org/abs/2403.03628
  • 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. https://personales.upv.es/thinkmind/dl/journals/sec/sec_v17_n12_2024/sec_v17_n12_2024_1.pdf
  • Schultenkämper, S., & Bäumer, F. S. (2024). Structured Knowledge Extraction for Digital Twins: Leveraging LLMs to Analyze Tweets. In F. Phillipson, G. Eichler, C. Erfurth, & G. Fahrnberger (Eds.), Innovations for Community Services. I4CS 2024. Communications in Computer and Information Science (Vol. 2109, pp. 150–165). Cham: Springer. https://doi.org/10.1007/978-3-031-60433-1_10
  • Semnani, P., Bogojeski, M., Bley, F., Zhang, Z., Wu, Q., Kneib, T., Herrmann, J., Weisser, C., Patcas, F., & Müller, K.-R. (2024). A Machine Learning and Explainable AI Framework Tailored for Unbalanced Experimental Catalyst Discovery. The Journal of Physical Chemistry C, 128(50), 21349–21367. https://doi.org/10.1021/acs.jpcc.4c05332
  • Stemmler, H., Lenel, F., Kis-Katos, K., & Weisser, C. (2024). Solar Technology as a Shock-Coping Device: Evidence from Rural Tanzania. SSRN. https://doi.org/10.2139/ssrn.5046518
  • Thielmann, A. F., Kumar, M., Weisser, C., Reuter, A., Säfken, B., & Samiee, S. (2024). Mambular: A Sequential Model for Tabular Deep Learning. arXiv. https://arxiv.org/abs/2408.06291
  • Thielmann, A., Reuter, A., Weisser, C., Kant, G., Kumar, M., & Säfken, B. (2024). STREAM: Simplified Topic Retrieval, Exploration, and Analysis Module. In Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers) (pp. 435–444). Bangkok, Thailand: Association for Computational Linguistics. https://doi.org/10.18653/v1/2024.acl-short.41
  • Thielmann, A., Weisser, C., & Säfken, B. (2024). Human in the Loop: How to Effectively Create Coherent Topics by Manually Labelling Only a Few Documents per Class. In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024) (pp. 8395–8405). https://aclanthology.org/2024.lrec-main.736/