TRR 318 - A dialog-based approach to explaining machine learning models (Subproject B01)
Overview
In Project B01, researchers are working on an artificial intelligence (AI) based system that can properly respond to questions at the level of language. In medicine, for example, the system should be able to explain a proposed treatment to a doctor and respond to patients’ questions and concerns regarding their treatment plan. The computer scientists and sociologists working on this project are including users’ perspectives in their research. For this, they are observing how, for instance, healthcare workers adopt this AI system and what requirements they have of the system. Based on these results, the researchers are developing a dialog system that can be used in a number of different areas of society.
Key Facts
- Grant Number:
- 438445824
- Project type:
- Forschung
- Project duration:
- 07/2021 - 06/2025
- Funded by:
- Deutsche Forschungsgemeinschaft (DFG)
- Website:
-
Homepage
More Information
Publications
Investigating Co-Constructive Behavior of Large Language Models in Explanation Dialogues
L. Fichtel, M. Splieth?ver, E. Hüllermeier, P. Jimenez, N. Klowait, S. Kopp, A.-C. Ngonga Ngomo, A. Robrecht, I. Scharlau, L. Terfloth, A.-L. Vollmer, H. Wachsmuth, ArXiv:2504.18483 (2025).
Dung’s Argumentation Framework: Unveiling the Expressive Power with Inconsistent Databases
Y. Mahmood, M. Hecher, A.-C. Ngonga Ngomo, Proceedings of the AAAI Conference on Artificial Intelligence 39 (2025) 15058–15066.
Logics with probabilistic team semantics and the Boolean negation
M. Hannula, M. Hirvonen, J. Kontinen, Y. Mahmood, A. Meier, J. Virtema, Journal of Logic and Computation 35 (2025).
Facets in Argumentation: A Formal Approach to Argument Significance
J. Fichte, N. Fr?hlich, M. Hecher, V. Lagerkvist, Y. Mahmood, A. Meier, J. Persson, ArXiv:2505.10982 (2025).
Why not? Developing ABox Abduction beyond Repairs
Show all publications
A.P.H. Haak, P. Koopmann, Y. Mahmood, A.-Y. Turhan, ArXiv:2507.21955 (2025).