Expressive Explanations of DNNs by Combining Concept Analysis with ILP. - Johannes Rabold; Gesina Schwalbe; Ute Schmid (KI, 2020)

Structuring the Safety Argumentation for Deep Neural Network Based Perception in Automotive Applications. - Gesina Schwalbe; Bernhard Knie; Timo Sämann; Timo Dobberphul; Lydia Gauerhof; Shervin Raafatnia; Vittorio Rocco (SAFECOMP Workshops, 2020)

Verification of Size Invariance in DNN Activations Using Concept Embeddings. - Gesina Schwalbe (AIAI, 2021)

Inspect, Understand, Overcome: A Survey of Practical Methods for AI Safety. - Sebastian Houben; Stephanie Abrecht; Maram Akila; Andreas Bär; Felix Brockherde; Patrick Feifel; Tim Fingscheidt; Sujan Sai Gannamaneni; Seyed Eghbal Ghobadi; Ahmed Hammam; Anselm Haselhoff; Felix Hauser; et al. (CoRR, 2021)

XAI Method Properties: A (Meta-)study. - Gesina Schwalbe; Bettina Finzel (CoRR, 2021)

Concept Embeddings for Fuzzy Logic Verification of Deep Neural Networks in Perception Tasks. - Gesina Schwalbe; Christian Wirth 001; Ute Schmid (CoRR, 2022)

Concept Embedding Analysis: A Review. - Gesina Schwalbe (CoRR, 2022)

Interpretable Model-Agnostic Plausibility Verification for 2D Object Detectors Using Domain-Invariant Concept Bottleneck Models. - Mert Keser; Gesina Schwalbe; Azarm Nowzad; Alois Knoll (CVPR Workshops, 2023)

Revealing Similar Semantics Inside CNNs: An Interpretable Concept-Based Comparison of Feature Spaces. - Georgii Mikriukov; Gesina Schwalbe; Christian Hellert; Korinna Bade (PKDD/ECML Workshops (1), 2023)

Evaluating the Stability of Semantic Concept Representations in CNNs for Robust Explainability. - Georgii Mikriukov; Gesina Schwalbe; Christian Hellert; Korinna Bade (xAI (2), 2023)

Quantified Semantic Comparison of Convolutional Neural Networks. - Georgii Mikriukov; Gesina Schwalbe; Christian Hellert; Korinna Bade (CoRR, 2023)

GCPV: Guided Concept Projection Vectors for the Explainable Inspection of CNN Feature Spaces. - Georgii Mikriukov; Gesina Schwalbe; Christian Hellert; Korinna Bade (CoRR, 2023)

Investigating Calibration and Corruption Robustness of Post-hoc Pruned Perception CNNs: An Image Classification Benchmark Study. - Pallavi Mitra; Gesina Schwalbe; Nadja Klein (CVPR Workshops, 2024)

Concept-Based Explanations in Computer Vision: Where Are We and Where Could We Go? - Jae Hee Lee 001; Georgii Mikriukov; Gesina Schwalbe; Stefan Wermter; Diedrich Wolter (ECCV Workshops (21), 2024)

Have We Ever Encountered This Before? Retrieving Out-of-Distribution Road Obstacles from Driving Scenes. - Youssef Shoeb; Robin Chan; Gesina Schwalbe; Azarm Nowzad; Fatma Güney; Hanno Gottschalk (WACV, 2024)

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

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

Unveiling Ontological Commitment in Multi-Modal Foundation Models. - Mert Keser; Gesina Schwalbe; Niki Amini-Naieni; Matthias Rottmann; Alois Knoll (CoRR, 2024)

A comprehensive taxonomy for explainable artificial intelligence: a systematic survey of surveys on methods and concepts. - Gesina Schwalbe; Bettina Finzel (Data Min. Knowl. Discov., 2024)

Benchmarking Vision Foundation Models for Input Monitoring in Autonomous Driving. - Mert Keser; Halil Ibrahim Orhan; Niki Amini-Naieni; Gesina Schwalbe; Alois Knoll; Matthias Rottmann (CoRR, 2025)

On Background Bias of Post-Hoc Concept Embeddings in Computer Vision DNNs. - Gesina Schwalbe; Georgii Mikriukov; Edgar Heinert; Stavros Gerolymatos; Mert Keser; Alois Knoll; Matthias Rottmann; Annika Mütze (CoRR, 2025)

Local Concept Embeddings for Analysis of Concept Distributions in Vision DNN Feature Spaces. - Georgii Mikriukov; Gesina Schwalbe; Korinna Bade (Int. J. Comput. Vis., 2025)