Professorship for Information Systems, in particular Artificial Intelligence and Explainability
Organisational unit: Professoship
Organisation profile
The research group on Artificial Intelligence and Explainability focuses on hybrid AI methods to make machines understand human-created data. That is, we combine modern, sub-symbolic machine learning approaches with symbolic knowledge engineering based on Knowledge Graphs to develop transparent AI systems. We focus on Knowledge Extraction, Speech Assistants, Question Answering, AI ethics, and more.
31 - 32 out of 32Page size: 10
- Published
Bridge-Generate: Scholarly Hybrid Question Answering
Taffa, T. A. & Usbeck, R., 2025, WWW Companion’25: Companion Proceedings of the ACM Web Conference 2025, April 28-May 2, 2025 Sydney, NSW, Australia. Long, G., Blumestein, M., Chang, Y., Lewin-Eytan, L., Huang, H. & Yom-Tov, E. (eds.). New York: Association for Computing Machinery, Inc, p. 1321-1325 5 p.Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
- Published
Ontology-Guided, Hybrid Prompt Learning for Generalization in Knowledge Graph Question Answering
Jiang, L., Huang, J., Möller, C. & Usbeck, R., 06.02.2025Research output: other publications › Other › Research