Introducing a Multi-Perspective xAI Tool for Better Model Explainability. - Marek Pawlicki; Damian Puchalski; Sebastian Szelest; Aleksandra Pawlicka; Rafal Kozik; Michal Choras (ARES, 2024)

ExpLEA-AIner: Proposition and Development of the Model-Driven Approach to Incorporating Explainable AI in Network Intrusion Detection Systems for Law Enforcement Agencies. - Marek Pawlicki; Aleksandra Pawlicka; Sebastian Szelest; Mikolaj Komisarek; Rafal Kozik; Michal Choras (EMCIS (2), 2024)

Proposition of a Novel Type of Attacks Targetting Explainable AI Algorithms in Cybersecurity. - Sebastian Szelest; Marek Pawlicki; Aleksandra Pawlicka; Rafal Kozik; Michal Choras (ESORICS Workshops (2), 2024)

Class-Based SHAP Analysis for Improved Explainability Insights in NIDS. - Marek Pawlicki; Aleksandra Pawlicka; Sebastian Szelest; Rafal Kozik; Michal Choras (ICAI (1), 2024)

Evaluating the necessity of the multiple metrics for assessing explainable AI: A critical examination. - Marek Pawlicki; Aleksandra Pawlicka; Federica Uccello; Sebastian Szelest; Salvatore D'Antonio; Rafal Kozik; Michal Choras (Neurocomputing, 2024)

SHAP Insights into Domain Adaptation in Netflow-Based Network Intrusion Detection Powered by Deep Learning. - Marek Pawlicki; Sebastian Szelest; Rafal Kozik; Michal Choras (ARES (EU Projects Symposium Workshops 2), 2025)