2026

• Berger, U., Biehler, R., Binder, K., Elmer, C., Ertz, F., Hotz, T., Huber, S., Ickstadt, K., Kauermann, G., Küchenhoff, H., Lübke, K., Münnich, R., Schüller, K., Skill, T., Weihs, C., Weinert, H., & Weisser, C. (2026). Daten, Künstliche Intelligenz und Evidenz – neue Anforderungen an die Statistikausbildung an Hochschulen: Diskussion und Erwiderung. AStA Wirtschafts- und Sozialstatistisches Archiv. https://doi.org/10.1007/s11943-026-00372-0
• Kumar, M., Thielmann, A. F., Weisser, C., & Säfken, B. (2026). From Uniform to Learned Knots: A Study of Spline-Based Numerical Encodings for Tabular Deep Learning. arXiv. https://arxiv.org/abs/2604.05635
• Lukassen, F., Herrmann, J., Weisser, C., Silbersdorff, A., Säfken, B., & Kneib, T. (2026). Quality Without Usefulness: LLM-Generated XAI Narratives as Trust Heuristics Rather Than Decision Aids. arXiv. https://arxiv.org/abs/2605.26770
• Lukassen, F., Herrmann, J., Weisser, C., Säfken, B., & Kneib, T. (2026). From XAI to Stories: A Factorial Study of LLM-Generated Explanation Quality. arXiv. https://arxiv.org/abs/2601.02224
• Lukassen, F., Weisser, C., Kneib, T., & Silbersdorff, A. (2026). CAFE: A Compound-AI Factorial Evaluation Framework. arXiv. https://arxiv.org/abs/2607.10380
• Lukassen, F., Weisser, C., Schlee, M., Kumar, M., Thielmann, A., Säfken, B., Silbersdorff, A., & Kneib, T. (2026). LLM-Augmented Changepoint Detection: A Framework for Ensemble Detection and Automated Explanation. arXiv. https://arxiv.org/abs/2601.02957
• Paredes Amorin, A., Python, A., & Weisser, C. (2026). Not All News Is Equal: Topic- and Event-Conditional Sentiment from Finetuned LLMs for Aluminum Price Forecasting. In LREC 2026 – The Fifteenth Biennial Language Resources and Evaluation Conference: Financial Narrative Processing (FNP) Workshop. https://arxiv.org/abs/2603.09085
• Schlee, M., Weisser, C., Kivimäki, T., Mashiku, M., & Säfken, B. (2026). LabelFusion: Learning to Fuse LLMs and Transformer Classifiers for Robust Text Classification. In LREC 2026 – The Fifteenth Biennial Language Resources and Evaluation Conference: Financial Narrative Processing (FNP) Workshop. https://arxiv.org/abs/2512.10793
• Schultenkämper, S., & Bäumer, F. S. (2026). Information Disclosure on the Web: Developing a Threat Model for the Digital Twin. In Proceedings of the 2026 International Conference on Semantic Computing (ICSC) (pp. 366–371). https://doi.org/10.1109/ICSC67292.2026.00061
• Schultenkämper, S., & Bäumer, F. S. (2026). Synthetic Personas for Social Networks: Census Demographics with LLM-Generated Behavior. In International Conference on Information and Software Technologies (ICIST 2026). Springer. In Press.
• Vovchenko, V., Barberi, V., Schultenkämper, S., & Bäumer, F. S. (2026). ADRIAN InstructFace-Edit – Towards Robust Detection of AI-Manipulated Face Images. In The First International Conference on Security and Cybersecurity in the AI and Digital Context. DTR Society Press. In Press.
• Vovchenko, V., Schultenkämper, S., & Bäumer, F. S. (2026). A Web-Based Platform for Interactive Comparison of Neural Network Image Segmentation Models. In AIMEDIA 2026: The Second International Conference on AI-based Media Innovation. IARIA. In Press.