The XAI paradox: Systems that Perform Well for the Wrong Reasons. - Cor Steging; Lambert Schomaker; Bart Verheij (BNAIC/BENELEARN, 2019)

Discovering the rationale of decisions: towards a method for aligning learning and reasoning. - Cor Steging; Silja Renooij; Bart Verheij (ICAIL, 2021)

Discovering the Rationale of Decisions: Experiments on Aligning Learning and Reasoning. - Cor Steging; Bart Verheij; Silja Renooij (XAILA@ICAIL, 2021)

Rationale Discovery and Explainable AI. - Cor Steging; Silja Renooij; Bart Verheij (JURIX, 2021)

Discovering the Rationale of Decisions. - Cor Steging; Silja Renooij; Bart Verheij (HHAI, 2022)

Design of Responsible Hybrid Intelligence (Preface). - Ludi van Leeuwen; Cor Steging; Bart Verheij (HHAI Workshops, 2023)

Taking the Law More Seriously by Investigating Design Choices in Machine Learning Prediction Research. - Cor Steging; Silja Renooij; Bart Verheij (ASAIL@ICAIL, 2023)

Improving Rationales with Small, Inconsistent and Incomplete Data. - Cor Steging; Silja Renooij; Bart Verheij (JURIX, 2023)

Arguments, rules and cases in law: Resources for aligning learning and reasoning in structured domains. - Cor Steging; Silja Renooij; Bart Verheij; Trevor J. M. Bench-Capon (Argument Comput., 2023)

Parameterized Argumentation-based Reasoning Tasks for Benchmarking Generative Language Models. - Cor Steging; Silja Renooij; Bart Verheij (CoRR, 2025)

Toward Reasonable Parrots: Why Large Language Models Should Argue with Us by Design. - Elena Musi; Nadin Kokciyan; Khalid Al-Khatib; Davide Ceolin; Emmanuelle Dietz; Klara Gutekunst; Annette Hautli-Janisz; Cristian Manuel Santibañez Yañez; Jodi Schneider; Jonas Scholz; Cor Steging; Jacky Visser; et al. (CoRR, 2025)