Coping with Data Distribution Shifts: XAI-Based Adaptive Learning with SHAP Clustering for Energy Consumption Prediction. - Tobias Clement; Truong Thanh Hung Nguyen; Nils Kemmerzell; Mohamed Abdelaal 001; Davor Stjelja (AI (2), 2023)

Disentangling the Linguistic Competence of Privacy-Preserving BERT. - Stefan Arnold; Nils Kemmerzell; Annika Schreiner (BlackboxNLP@EMNLP, 2023)

XAIR: A Systematic Metareview of Explainable AI (XAI) Aligned to the Software Development Process. - Tobias Clement; Nils Kemmerzell; Mohamed Abdelaal 001; Michael Amberg (Mach. Learn. Knowl. Extr., 2023)

Towards a Quantitative Evaluation Framework for Trustworthy AI in Facial Analysis. - Annika Schreiner; Nils Kemmerzell (HICSS, 2024)

LangXAI: Integrating Large Vision Models for Generating Textual Explanations to Enhance Explainability in Visual Perception Tasks. - Truong Thanh Hung Nguyen; Tobias Clement; Phuc Truong Loc Nguyen; Nils Kemmerzell; Van Binh Truong; Vo Thanh Khang Nguyen; Mohamed Abdelaal 001; Hung Cao (IJCAI, 2024)

Quantifying the Trade-Offs Between Dimensions of Trustworthy AI - An Empirical Study on Fairness, Explainability, Privacy, and Robustness. - Nils Kemmerzell; Annika Schreiner (KI, 2024)

Beyond explaining: XAI-based Adaptive Learning with SHAP Clustering for Energy Consumption Prediction. - Tobias Clement; Truong Thanh Hung Nguyen; Nils Kemmerzell; Mohamed Abdelaal 001; Davor Stjelja (CoRR, 2024)

Unveiling Privacy Risks in WebGPU through Hardware-based Device Fingerprinting. - Konrad Hohentanner; Nils Kemmerzell; Steffen Florschütz (WISEC, 2025)

Towards a Better Understanding of Evaluating Trustworthiness in AI Systems. - Nils Kemmerzell; Annika Schreiner; Haroon Khalid; Michael Schalk; Letizia Bordoli (ACM Comput. Surv., 2025)