Measurably Stronger Explanation Reliability Via Model Canonization. - Franz Motzkus; Leander Weber; Sebastian Lapuschkin (ICIP, 2022)

Quantus: An Explainable AI Toolkit for Responsible Evaluation of Neural Network Explanations. - Anna Hedström; Leander Weber; Dilyara Bareeva; Franz Motzkus; Wojciech Samek; Sebastian Lapuschkin; Marina M.-C. Höhne (CoRR, 2022)

Quantus: An Explainable AI Toolkit for Responsible Evaluation of Neural Network Explanations and Beyond. - Anna Hedström; Leander Weber; Daniel Krakowczyk; Dilyara Bareeva; Franz Motzkus; Wojciech Samek; Sebastian Lapuschkin; Marina M.-C. Höhne (J. Mach. Learn. Res., 2023)

Unveiling the Anatomy of Adversarial Attacks: Concept-Based XAI Dissection of CNNs. - Georgii Mikriukov; Gesina Schwalbe; Franz Motzkus; Korinna Bade (xAI (1), 2024)

Locally Testing Model Detections for Semantic Global Concepts. - Franz Motzkus; Georgii Mikriukov; Christian Hellert; Ute Schmid (xAI (1), 2024)

The Anatomy of Adversarial Attacks: Concept-based XAI Dissection. - Georgii Mikriukov; Gesina Schwalbe; Franz Motzkus; Korinna Bade (CoRR, 2024)

CoLa-DCE - Concept-guided Latent Diffusion Counterfactual Explanations. - Franz Motzkus; Christian Hellert; Ute Schmid (CoRR, 2024)