Discrete Diffusion-Based Model-Level Explanation of Heterogeneous GNNs with Node Features
P. Das, S. Heindorf, in: Proceedings of the ACM Web Conference 2026 (WWW ’26), ACM, 2026.

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.

ROCES: Robust Class Expression Synthesis in Description Logics via Iterative Sampling
N.J. KOUAGOU, S. Heindorf, C. Demir, A.-C. Ngonga Ngomo, in: Proceedings of the Thirty-ThirdInternational Joint Conference on Artificial Intelligence, International Joint Conferences on Artificial Intelligence Organization, 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.

AI-Based Assistance System for Manufacturing
S. Deppe, L. Brandt, M. Brünninghaus, J. Papenkordt, S. Heindorf, G. Tschirner-Vinke, (2022).

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.

EvoLearner: Learning Description Logics with Evolutionary Algorithms
S. Heindorf, L. Blübaum, N. Düsterhus, T. Werner, V.N. Golani, C. Demir, A.-C. Ngonga Ngomo, in: WWW, ACM, 2022, pp. 818–828.

CovidPubGraph: A FAIR Knowledge Graph of COVID-19 Publications
S. Pestryakova, D. Vollmers, M. Sherif, S. Heindorf, M. Saleem, D. Moussallem, A.-C. Ngonga Ngomo, Scientific Data (2022).