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Bridging the Disciplinary Gap in Explainable AI: From Abstract Desiderata to Concrete Tasks
Hanwei Zhang, Jingwen Wang, Holger Hermanns
Explainable AI (XAI) is often criticized for failing to satisfy broad desiderata (e.g., fairness, accountability) and for limited practical value to stakeholders. This challenge pa…
Over-approximation of weakly-hard constraints for control systems verification (Extended)
Rieke de Maeyer, Holger Hermanns, Martina Maggio
A hard real-time system cannot miss any deadline. A weakly-hard real-time system, on the contrary, is designed to tolerate a specific number of deadline misses. For instance, the A…
SL-CBM: Enhancing Concept Bottleneck Models with Semantic Locality for Better Interpretability
Hanwei Zhang, Luo Cheng, Rui Wen +3
Explainable AI (XAI) is crucial for building transparent and trustworthy machine learning systems, especially in high-stakes domains. Concept Bottleneck Models (CBMs) have emerged…