The Data Science Chair (computer science institute JMU) is a highly interdisciplinary group of researchers led by Prof. Andreas Hotho and member of CAIDAS. We are active in data science and machine learning research with focus on deep learning and applications in multiple domains.
Address
University of Würzburg Data Science Chair (Computer Science X) Emil-Fischer-Straße 50 97074 Würzburg
TaylorNet: Learning PDEs from Non-Grid DataA. Dulny; P. Heinisch; A. Hotho; A. Krause in Proceedings of Machine Learning Research, C. Coelho, B. Zimmering, M. F. P. Costa, L. L. Ferrás, O. Niggemann (Eds.) (2025). (Vol. 277) 26–46.
Die SuperGLEBer at GermEval 2025 Shared Tasks: Growing Pains - When More Isn’t Always BetterJ. Wunderle; J. Pfister; A. Hotho C. Wartena, U. Heid (Eds.) (2025). 479–493.
BARTABSA++: Revisiting BARTABSA with Decoder LLMsJ. Pfister; T. Völker; A. Vlasjuk; A. Hotho H. Fei, K. Tu, Y. Zhang, X. Hu, W. Han, Z. Jia, Z. Zheng, Y. Cao, M. Zhang, W. Lu, N. Siddharth, L. Ovrelid, N. Xue, Y. Zhang (Eds.) (2025). 115–128.
LLäMmlein: Transparent, Compact and Competitive German-Only Language Models from ScratchJ. Pfister; J. Wunderle; A. Hotho W. Che, J. Nabende, E. Shutova, M. T. Pilehvar (Eds.) (2025). 2227–2246.
SALT at SemEval-2025 Task 2: A SQL-based Approach for LLM-Free Entity-Aware-TranslationT. Völker; J. Pfister; A. Hotho S. Rosenthal, A. Rosá, D. Ghosh, M. Zampieri (Eds.) (2025). 852–864.
CAIDAS at SemEval-2025 Task 7: Enriching Sparse Datasets with LLM-Generated Content for Improved Information RetrievalD. Benchert; S. Meßlinger; S. Goller; J. Kaiser; J. Pfister; A. Hotho S. Rosenthal, A. Rosá, D. Ghosh, M. Zampieri (Eds.) (2025). 1623–1638.
Modeling and Analyzing the Influence of Non-Item Pages on Sequential Next-Item PredictionE. Fischer; A. Zehe; A. Hotho; D. Schlör in ACM Trans. Recomm. Syst. (2025).
Enriching Large Language Models with Knowledge Graphs for Computational Literary StudiesT. Hagen; J. Omeliyanenko; A. Ehrmanntraut; A. Hotho; A. Zehe; F. Jannidis in Handbook on Neurosymbolic AI and Knowledge Graphs (2025).
PreAdapter: Pre-training Language Models on Knowledge GraphsJ. Omeliyanenko; A. Hotho; D. Schlör G. Demartini, K. Hose, M. Acosta, M. Palmonari, G. Cheng, H. Skaf-Molli, N. Ferranti, D. Hernández, A. Hogan (Eds.) (2025). 210–226.
Identifying Axiomatic Mathematical Transformation Steps using Tree-Structured Pointer NetworksS. Wankerl; J. Pfister; A. Dulny; G. Götz; A. Hotho in Transactions on Machine Learning Research (2025).
Adapting Sequential Recommender Models to Content Recommendation in Chat Data using Non-Item Page-ModelsA. Zehe; E. Fischer; J. Kaiser; T. Wagner; A. Hotho (2024).
Bayesian Inference for Composition of Hypotheses in Sequential Data. Technical Report (Master thesis), M. J. Levermann PhD thesis, Julius-Maximilians-Universität Würzburg, Professur für Inverse Probleme. (2024, September 28).
OtterlyObsessedWithSemantics at SemEval-2024 Task 4: Developing a Hierarchical Multi-Label Classification Head for Large Language ModelsJ. Wunderle; J. Schubert; A. Cacciatore; A. Zehe; J. Pfister; A. Hotho A. K. Ojha, A. S. Dougruöz, H. Tayyar Madabushi, G. Da San Martino, S. Rosenthal, A. Rosá (Eds.) (2024). 602–612.
We presented a keynote on our LLäMmlein and ModernGBERT models at the German National Library in Frankfurt, as part of the "Netzwerk maschinelle Verfahren in der Erschließung" symposium.
We, the Data Science Chair and the Chair of Computer Philology and Modern German Literary History at CAIDAS, are part of the new large-scale project „Sovereign Open Source Foundational Models for European Intelligence“ (SOOFI)
