Beyond One-Shot Explanations: A Systematic Literature Review of Dialogue-Based XAI Approaches
D. Mindlin, F. Beer, L.N. Sieger, S. Heindorf, P. Cimiano, E. Esposito, A.-C. Ngonga Ngomo, Artificial Intelligence Review 58 (2025).

Assessing Natural Language Explanations of Relational Graph Neural Networks
S. Heindorf, D. Neib, in: Proceedings of the 34th ACM International Conference on Information and Knowledge Management, ACM, 2025.

Universal Knowledge Graph Embeddings
N.J. KOUAGOU, C. Demir, H.M.A. Zahera, A. Wilke, S. Heindorf, J. Li, A.-C. Ngonga Ngomo, in: Companion Proceedings of the ACM on Web Conference 2024, ACM, 2024.

Utilizing Description Logics for Global Explanations of Heterogeneous  Graph Neural Networks
D. Köhler, S. Heindorf, ArXiv:2405.12654 (2024).

Causal Question Answering with Reinforcement Learning
L. Blübaum, S. Heindorf, in: The World Wide Web Conference (WWW), ACM, n.d., pp. 2204–2215.

EDGE: Evaluation Framework for Logical vs. Subgraph Explanations for Node Classifiers on Knowledge Graphs
R. Sapkota, D. Köhler, S. Heindorf, in: Proceedings of the 33rd ACM International Conference on Information and Knowledge Management (CIKM ’24), ACM, Boise, Idaho, USA, 2024.

AutoCL: AutoML for Concept Learning
J. Li, S. Satheesh, S. Heindorf, D. Moussallem, R. Speck, A.-C. Ngonga Ngomo, in: Communications in Computer and Information Science, Springer Nature Switzerland, Cham, 2024.

Class Expression Learning with Multiple Representations
A.-C. Ngonga Ngomo, C. Demir, N.J. Kouagou, S. Heindorf, N. Karalis, A. Bigerl, in: Compendium of Neurosymbolic Artificial Intelligence, IOS Press, 2023, pp. 272–286.

LitCQD: Multi-Hop Reasoning in Incomplete Knowledge Graphs with Numeric Literals
C. Demir, M. Wiebesiek, R. Lu, A.-C. Ngonga Ngomo, S. Heindorf, ECML PKDD (2023).

Neural Class Expression Synthesis in ALCHIQ(D)
N.J. Kouagou, S. Heindorf, C. Demir, A.-C. Ngonga Ngomo, in: Machine Learning and Knowledge Discovery in Databases: Research Track, Springer Nature Switzerland, Cham, 2023.

Explaining ELH Concept Descriptions through Counterfactual Reasoning
L.N. Sieger, S. Heindorf, L. Blübaum, A.-C. Ngonga Ngomo, ArXiv:2301.05109 (2023).

Neural Class Expression Synthesis (Extended Abstract)
N.J. KOUAGOU, S. Heindorf, C. Demir, A.-C. Ngonga Ngomo, in: NeSy 2023, 17th International Workshop on Neural-Symbolic Learning and Reasoning, Certosa Di Pontignano, Siena, Italy, CEUR-WS, 2023.

Neural Class Expression Synthesis
N.J. KOUAGOU, S. Heindorf, C. Demir, A.-C. Ngonga Ngomo, in: C. Pesquita, E. Jimenez-Ruiz, J. McCusker, D. Faria, M. Dragoni, A. Dimou, R. Troncy, S. Hertling (Eds.), The Semantic Web - 20th Extended Semantic Web Conference (ESWC 2023), Springer International Publishing, 2023, pp. 209–226.

Accelerating Concept Learning via Sampling
A. Baci, S. Heindorf, in: CIKM, 2023, pp. 3733–3737.

Learning Concept Lengths Accelerates Concept Learning in ALC
N.J. KOUAGOU, S. Heindorf, C. Demir, A.-C. Ngonga Ngomo, in: The Semantic Web, Springer International Publishing, Cham, 2022.

User Involvement in Training Smart Home Agents
L.N. Sieger, J. Hermann, A. Schomäcker, S. Heindorf, C. Meske, C.-C. Hey, A. Dofangün, in: International Conference on Human-Agent Interaction, ACM, 2022.

CausalQA: A Benchmark for Causal Question Answering
A. Bondarenko, M. Wolska, S. Heindorf, L. Blübaum, A.-C. Ngonga Ngomo, B. Stein, P. Braslavski, M. Hagen, M. Potthast, in: Proceedings of the 29th International Conference on Computational Linguistics, International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 2022, pp. 3296–3308.