Publications

• Effrosyni Sokli, Pranav Kasela, Georgios Peikos, and Gabriella Pasi: Mixture of Experts Approaches in Dense Retrieval Tasks. In Proceedings of the 2025 IEEE/WIC International Conference on Web Intelligence and Intelligent Agent Technology. (WI-IAT 2025, pdf, Best Paper Award)
• Louis Mozart Kamdem Teyou, Luke Friedrichs, N'Dah Jean Kouagou, Caglar Demir, Yasir Mahmood, Stefan Heindorf, and Axel-Cyrille Ngonga Ngomo: Neural Reasoning for Robust Instance Retrieval in SHOIQ. Accepted, to appear in the proceedings of the Thirteenth International Conference on Knowledge Capture (K-CAP 2025, HTML version)
• Marco Grillo, Wojciech Kotłowski, and Miłosz Kadziński: Ordinal regression meets online learning: Interactive preference learning for multiple criteria choice and ranking with provable guarantees. In European Journal of Operational Research. (EJOR, pdf)
• Jonas Hanselle, Alireza Javanmardi, Tobias Florin Oberkofler, Yusuf Sale, and Eyke Hüllermeier: Conformal prediction without nonconformity scores. In Proceedings of the Forty-first Conference on Uncertainty in Artificial Intelligence (UAI 2025, pdf)
• Effrosyni Sokli, Georgios Peikos, Pranav Kasela, and Gabriella Pasi: Leveraging Cognitive Complexity of Texts for Contextualization in Dense Retrieval. In Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing. (EMNLP 2025, pdf)
• C. Shimillas, K. Malialis, K. Fokianos, and M. M. Polycarpou: Transformer-Based Multivariate Time Series Anomaly Localization. 2025 IEEE Symposium on Computational Intelligence on Engineering/Cyber Physical Systems (CIES 2025, pdf, Outstanding Paper Award)
• Rodrigo Castellano Ontiveros, Francesco Giannini, Marco Gori, Giuseppe Marra, and Michelangelo Diligenti: Grounding Methods for Neural-Symbolic AI. Accepted, to appear in the proceedings (IJCAI 2025, pdf)
• Rodrigo Castellano Ontiveros, Francesco Giannini, and Michelangelo Diligenti: Distilling KGE black boxes into interpretable NeSy models. Accepted, to appear in the proceedings (NeSy 2025, pdf)
• Rodrigo Castellano Ontiveros, Ehsan Bonabi Mobaraki, Francesco Giannini, Pietro Barbiero, Marco Gori, and Michelangelo Diligenti: Interpretable-by-design Neural-Symbolic Link Prediction on Knowledge Graphs. Accepted, to appear in the proceedings (XAI-2025, pdf)
• Isaac Roberts, Fabian Hinder, Valerie Vaquet, Alexander Schulz, Barbara Hammer: Conceptualizing Concept Drift. In ESANN 2025 Proceedings. (ESANN 2025, pdf)
• Fabian Hoppe, Filip Ilievski, and Jan-Christoph Kalo: Investigating the Robustness of Deductive Reasoning with Large Language Models. In ArXiv 2025 (Preprint, pdf)
• Ying Jiao, Luc De Raedt, and Giuseppe Marra: Valid Text-to-SQL Generation with Unification-Based DeepStochLog. In: Besold, T.R., d’Avila Garcez, A., Jimenez-Ruiz, E., Confalonieri, R., Madhyastha, P., Wagner, B. (eds) Neural-Symbolic Learning and Reasoning. (NeSy 2024, pdf)
• Isaac Roberts, Alexander Schulz, Sarah Schroeder, Luca Hermes, and Barbara Hammer: Targeted Visualization of the Backbone of Encoder LLMs. In ECML Workshop AIMLAI: Workshop on Advances in Interpretable Machine Learning and Artificial Intelligence. In Press 2024. (ECML 2024, pdf)
• Louis Mozart Kamdem Teyou, Caglar Demir, Axel-Cyrille Ngonga Ngomo: Embedding Knowledge Graphs in Degenerate Clifford Algebras. In Proceedings of the European Conference of Artificial Intelligence (ECAI 2024, pdf)
• Louis Mozart Kamdem Teyou, Caglar Demir, Axel-Cyrille Ngonga Ngomo: Embedding Knowledge Graphs in Function Spaces. In Proceedings of the International Conference on Information and Knowledge Management (CIKM 2024, pdf)
• Andreas Mazur, Jay (Isaac) Roberts, David Leins, Alexander Schulz, Barbara Hammer: Visualizing and Improving 3D Mesh Segmentation with DeepView. In ESANN 2024 Proceedings. (ESANN 2024, pdf)
• Effrosyni Sokli, Alessandro Raganato, Gabriella Pasi: Incorporating Cognitive Complexity of Text in Dense Retrieval for Personalized Search. In IIR 2024 Workshop. (IIR 2024, pdf)
• Taku Yamagata, Tobias Oberkofler, Timo Kaufmann, Viktor Bengs, Eyke Hüllermeier, Raul Santos-Rodriguez: Relatively Rational: Learning Utilities and Rationalities Jointly from Pairwise Preferences. In ICML 2024 Workshop on Models of Human Feedback for AI Alignment (ICML 2024, pdf)