Detecting subtle differences between human and model languages using spectrum of relative likelihood
Y. Xu, Y. Wang, H. An, Z. Liu, Y. Li, in: Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, ACL, Miami, FL, USA, 2024, pp. 10108–10121.

Multimodal Co-Construction of Explanations with XAI Workshop
H. Buschmeier, S. Kopp, T. Hassan, in: Proceedings of the 26th ACM International Conference on Multimodal Interaction, ACM, 2024, pp. 698–699.

A model of factors contributing to the success of dialogical explanations
M. Booshehri, H. Buschmeier, P. Cimiano, in: Proceedings of the 26th ACM International Conference on Multimodal Interaction, ACM, San José, Costa Rica, 2024, pp. 373–381.

Conversational feedback in scripted versus spontaneous dialogues: A comparative analysis
I. Pilán, L. Prévot, H. Buschmeier, P. Lison, in: Proceedings of the 25th Meeting of the Special Interest Group on Discourse and Dialogue, Kyoto, Japan, 2024, pp. 440–457.

Turn-taking dynamics across different phases of explanatory dialogues
P. Wagner, M. Wodarczak, H. Buschmeier, O. Türk, E. Gilmartin, in: Proceedings of the 28th Workshop on the Semantics and Pragmatics of Dialogue, Trento, Italy, 2024, pp. 6–14.

Blink: Blank Node Matching Using Embeddings
A. Becker, M. Sherif, A.-C. Ngonga Ngomo, in: Lecture Notes in Computer Science, Springer Nature Switzerland, Cham, 2024.

Efficient Evaluation of Conjunctive Regular Path Queries Using Multi-way Joins
N. Karalis, A. Bigerl, L. Heidrich, M. Sherif, A.-C. Ngonga Ngomo, in: ESWC, 2024.

PCFWebUI: Data-driven WebUI for holistic decarbonization based on PCF-Tracking
A. Kumar, M. Naumann, K. Henne, M. Sherif, in: D. Garijo, A.L. Gentile, A. Kurteva, A. Mannocci, F. Osborne, S. Vahdati (Eds.), Joint Proceedings of Posters, Demos, Workshops, and Tutorials of the 20th International Conference on Semantic Systems Co-Located with 20th International Conference on Semantic Systems (SEMANTiCS 2024), Amsterdam, The Netherlands, September 17-19, 2024, CEUR-WS.org, 2024.

Lehrkräftebildung in der digitalen Welt. Zukunftsorientierte Forschungs- und Praxisperspektiven 
B. Herzig, B. Eickelmann, F. Schwabl, J. Schulze, J. Niemann, eds., Lehrkräftebildung in der digitalen Welt. Zukunftsorientierte Forschungs- und Praxisperspektiven , 1st ed., Waxmann, Münster, 2024.

Lehrkräftebildung in der digitalen Welt. Zukunftsorientierte Forschungs- und Praxisperspektiven
B. Herzig, B. Eickelmann, F. Schwabl, J. Schulze, J. Niemann, eds., Lehrkräftebildung in der digitalen Welt. Zukunftsorientierte Forschungs- und Praxisperspektiven, 1st ed., Waxmann, Münster, 2024.

Generating SPARQL from Natural Language Using Chain-of-Thoughts Prompting
H.M.A. Zahera, A. Manzoor, M. Sherif, D. Moussallem, A.-C. Ngonga Ngomo, in: SEMANTiCS, Amsterdam, Netherlands, 2024.

Can AI explain AI? Interactive co-construction of explanations among human and artificial agents
N. Klowait, M. Erofeeva, M. Lenke, I. Horwath, H. Buschmeier, Discourse &; Communication 18 (2024) 917–930.

No learning rates needed: Introducing SALSA - Stable Armijo Line Search Adaptation
P. Kenneweg, T. Kenneweg, F. Fumagalli, B. Hammer, in: 2024 International Joint Conference on Neural Networks (IJCNN), 2024, pp. 1–8.

Beyond TreeSHAP: Efficient Computation of Any-Order Shapley Interactions for Tree Ensembles
M. Muschalik, F. Fumagalli, B. Hammer, E. Huellermeier, in: Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2024, pp. 14388–14396.

SVARM-IQ: Efficient Approximation of Any-order Shapley Interactions through Stratification
P. Kolpaczki, M. Muschalik, F. Fumagalli, B. Hammer, E. Huellermeier, in: Proceedings of The 27th International Conference on Artificial Intelligence and Statistics (AISTATS), PMLR, 2024, pp. 3520–3528.

KernelSHAP-IQ: Weighted Least Square Optimization for Shapley Interactions
F. Fumagalli, M. Muschalik, P. Kolpaczki, E. Hüllermeier, B. Hammer, in: Proceedings of the 41st International Conference on Machine Learning (ICML), PMLR, 2024, pp. 14308–14342.

shapiq: Shapley interactions for machine learning
M. Muschalik, H. Baniecki, F. Fumagalli, P. Kolpaczki, B. Hammer, E. Huellermeier, in: Advances in Neural Information Processing Systems (NeurIPS), 2024, pp. 130324–130357.

Approximating the shapley value without marginal contributions
P. Kolpaczki, V. Bengs, M. Muschalik, E. Hüllermeier, in: Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2024, pp. 13246–13255.

Quote to explain: Using multimodal metalinguistic markers to explain large language models’ understanding capabilities
M. Belosevic, H. Buschmeier, in: ICMI Companion ’24: Companion Proceedings of the 26th International Conference on Multimodal Interaction, ACM, San José, Costa Rica, 2024, pp. 225–227.

Revisiting the phenomenon of syntactic complexity convergence on German dialogue data
Y. Wang, H. Buschmeier, in: Proceedings of the 20th Conference on Natural Language Processing (KONVENS 2024), Vienna, Austria, 2024, pp. 75–80.