9.00-9.15 Welcome
9.15-10.00 Session 1 - Keynote
Paul Groth. Co-Constructing Explanations for AI Systems using Provenance
10.00-10.30 Session 2 - Transparency and Explainability in Knowledge Graphs
Vidhya Kamakshi and Chandramani Chaudhary.
Towards Transparent Knowledge Graphs: A Position on Explainability in Link Prediction.
Luisa Vollmer, Rébecca Loubet, Fabian Jirasek, Hans Hasse, Sophie Fellenz and Heike Leitte.
Enabling Transparent Problem Solving in Thermodynamics with Ontologies and Knowledge Graphs.
10.30-11.00 Coffee break
11.00-12.30 Session 3 - Advances in Knowledge Graph Applications and Interpretability
Lukas Gehring, Moritz Blum, Basil Ell and Philipp Cimiano.
Path of Time: Explanations for Temporal Knowledge Graph Completion through Chronological Regulation.
Lenka Tětková, Teresa Dorszewski, Maria Mandrup Fogh, Ellen Marie Gaunby Jørgensen, Finn Årup Nielsen and Lars Kai Hansen.
Knowledge Graphs for Empirical Concept Retrieval.
Manas Madine.
Attention Sink Is Sinking Causality: Causal Interpretation of Self-Attention in Decoder Language Models and Mitigating Attention Sink for Improved Interpretability.
Peter Kardos, Richárd Farkas and András London.
Human-in-the-loop Entity Set Expansion using Knowledge Graphs.
Victoria Firsanova and Yana Khlusova.
AGGILE: Automated Graph Generation for Inference and Language Exploration.
12.30-12.35 Closing