Data Science Chair

About Us

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

We have moved! We're now located at:

University of Würzburg
Data Science Chair (Computer Science X)
Emil-Fischer-Straße 50
97074 Würzburg

Phone.: +49 931 31-89675
sekretariat.lsx@uni-wuerzburg.de

We are part of:

Recent Publications

Pollice Verso at {S}em{E}val-2024 Task 6: The {R}oman Empire Strikes Back. Kobs, Konstantin; Pfister, Jan; Hotho, Andreas. In Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024), A. K. Ojha, A. S. Do{\u{g}}ru{ö}z, H. Tayyar Madabushi, G. Da San Martino, S. Rosenthal, A. Ros{á} (eds.), pp. 1529–1536. Association for Computational Linguistics, Mexico City, Mexico, 2024
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{S}uper{GLEB}er: {G}erman Language Understanding Evaluation Benchmark. Pfister, Jan; Hotho, Andreas. In Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), K. Duh, H. Gomez, S. Bethard (eds.), pp. 7897–7916. Association for Computational Linguistics, Mexico City, Mexico, 2024
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{O}tterly{O}bsessed{W}ith{S}emantics at {S}em{E}val-2024 Task 4: Developing a Hierarchical Multi-Label Classification Head for Large Language Models. Wunderle, Julia; Schubert, Julian; Cacciatore, Antonella; Zehe, Albin; Pfister, Jan; Hotho, Andreas. In Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024), A. K. Ojha, A. S. Do{\u{g}}ru{ö}z, H. Tayyar Madabushi, G. Da San Martino, S. Rosenthal, A. Ros{á} (eds.), pp. 602–612. Association for Computational Linguistics, Mexico City, Mexico, 2024
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From Chat to Publication Management: Organizing your related work using BibSonomy & LLMs. Völker, Tom; Pfister, Jan; Koopmann, Tobias; Hotho, Andreas. In Proceedings of the 2024 Conference on Human Information Interaction and Retrieval, of CHIIR ’24, pp. 386–390. Association for Computing Machinery, <conf-loc>, <city>Sheffield</city>, <country>United Kingdom</country>, </conf-loc>, 2024
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Generative Inpainting for Shapley-Value-Based Anomaly Explanation. Tritscher, Julian; Lissmann, Philip; Wolf, Maximilian; Krause, Anna; Hotho, Andreas; Schlör, Daniel. In The World Conference on eXplainable Artificial Intelligence (xAI 2024) - to appear. 2024
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Marina: Realizing ML-Driven Real-Time Network Traffic Monitoring at Terabit Scale. Seufert, Michael; Dietz, Katharina; Wehner, Nikolas; Geißler, Stefan; Schüler, Joshua; Wolz, Manuel; Hotho, Andreas; Casas, Pedro; Hoßfeld, Tobias; Feldmann, Anja. In IEEE Transactions on Network and Service Management, pp. 1–1. 2024
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CompTrails: comparing hypotheses across behavioral networks. Koopmann, Tobias; Becker, Martin; Lemmerich, Florian; Hotho, Andreas. In Data Mining and Knowledge Discovery. 2024
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Global Vegetation Modeling with Pre-Trained Weather Transformers. Janetzky, Pascal; Gallusser, Florian; Hentschel, Simon; Hotho, Andreas; Krause, Anna. 2024
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From Chat to Publication Management: Organizing your related work using BibSonomy \& LLMs. V{ö}lker, Tom; Pfister, Jan; Koopmann, Tobias; Hotho, Andreas. In Proceedings of the 2024 Conference on Human Information Interaction and Retrieval, of CHIIR ’24, pp. 386–390. Association for Computing Machinery, <conf-loc>, <city>Sheffield</city>, <country>United Kingdom</country>, </conf-loc>, 2024
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BibSonomy Meets ChatLLMs for Publication Management: From Chat to Publication Management: Organizing your related work using BibSonomy & LLMs. Völker, Tom; Pfister, Jan; Koopmann, Tobias; Hotho, Andreas. 2024
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Liquor-HGNN: A heterogeneous graph neural network for leakage detection in water distribution networks. Schaller, Melanie; Steininger, Michael; Dulny, Andrzej; Schlör, Daniel; Hotho, Andreas. In LWDA’23: Lernen, Wissen, Daten, Analysen. October 09--11, 2023, Marburg, Germany, M. Leyer (ed.). 2023
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Multi-Task Transformer Visualization to build Trust for Clinical Outcome Prediction. Antweiler, Dario; Gallusser, Florian; Fuchs, Georg. In 2023 Workshop on Visual Analytics in Healthcare (VAHC), pp. 21–26. 2023
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Pointer Networks: A Unified Approach to Extracting {G}erman Opinions. Wunderle, Julia; Pfister, Jan; Hotho, Andreas. In Proceedings of the 19th Conference on Natural Language Processing (KONVENS 2023), M. Georges, A. Herygers, A. Friedrich, B. Roth (eds.), pp. 127–138. Association for Computational Lingustics, Ingolstadt, Germany, 2023
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Zero-Shot Clickbait Spoiling by Rephrasing Titles as Questions. Wangsadirdja, Dirk; Pfister, Jan; Kobs, Konstantin; Hotho, Andreas. In Proceedings of the The 17th International Workshop on Semantic Evaluation (SemEval-2023), pp. 1090–1095. Association for Computational Linguistics, Toronto, Canada, 2023
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Feature relevance XAI in anomaly detection: Reviewing approaches and challenges. Tritscher, Julian; Krause, Anna; Hotho, Andreas. In Frontiers in Artificial Intelligence, Vol. 6. 2023
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ConvMOS: climate model output statistics with deep learning. Steininger, Michael; Abel, Daniel; Ziegler, Katrin; Krause, Anna; Paeth, Heiko; Hotho, Andreas. In Data Mining and Knowledge Discovery, Vol. 37, Issue 1, pp. 136–166. 2023
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Evaluating feature relevance XAI in network intrusion detection. Tritscher, Julian; Wolf, Maximilian; Hotho, Andreas; Schlör, Daniel. In The World Conference on eXplainable Artificial Intelligence (xAI 2023). 2023
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Can Neural Networks Distinguish High-school Level Mathematical Concepts?. Wankerl, Sebastian; Dulny, Andrzej; Götz, Gerhard; Hotho, Andreas. In Accepted at ICDM. 2023
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Occupational Fraud Detection through Agent-based Data Generation. Tritscher, Julian; Roos, Alexander; Schlör, Daniel; Hotho, Andreas; Krause, Anna. In The 8th Workshop on MIning DAta for financial applicationS MIDAS 2023. 2023
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DynaBench: A Benchmark Dataset for Learning Dynamical Systems from Low-Resolution Data. Dulny, Andrzej; Hotho, Andreas; Krause, Anna. In Machine Learning and Knowledge Discovery in Databases: Research Track, D. Koutra, C. Plant, M. Gomez Rodriguez, E. Baralis, F. Bonchi (eds.), pp. 438–455. Springer Nature Switzerland, Cham, 2023
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News

Our paper "PreAdapter: Pre-training Language Models on Knowledge Graphs" has been accepted on ISWC 2024

Our paper proposes a novel adapter-based approach to integrate knowledge from knowledge graphs into large language models (LLMs).

Sucessful NAACL 2024

We had a succesful NAACL 2024 in Mexico City! We showcased "SuperGLEBer" - the first comprehensive German language benchmark, earned a best paper honorable mention with our hierarchical classifier, and even presented the Roman Empire's take on model hallucinations!

Our Paper "Data Generation for Explainable Occupational Fraud Detection" was accepted at KI 2024

In our paper, we use multi-agent systems to simulate labeled company data, allowing us to automatically detect and explain occupational fraud in otherwise unlabeled data.