Steging, C. (2024). Designing Responsible Artificial Intelligence: Hybrid Approaches for Aligning Learning and Reasoning. PhD thesis. PDF
Steging, C., van Leeuwen, L. (2024). A hybrid approach to legal textual entailment. In: Proceedings of the Eighteenth International Workshop on Juris-Informatics (JURISIN 2024), 154-169. Hamamatsu, Japan. PDF
Steging, C., Renooij, S., & Verheij, B. (2023). Improving Rationales with Small, Inconsistent and Incomplete Data. Legal Knowledge and Information Systems. JURIX 2023: The Thirty-sixth Annual Conference (ed. Sileno, G., Spanakis, J., van Dijck, G.), 53-62. Amsterdam: IOS Press. PDF
Steging, C., Renooij, S., & Verheij, B. (2023). Taking the Law More Seriously by Investigating Design Choices in Machine Learning Prediction Research. In: 6th Workshop on Automated Semantic Analysis of Information in Legal Text (ASAIL 2023), 49-59. CEUR Workshop Proceedings. PDF
Steging, C., Renooij, S., & Verheij, B. (2023). Arguments, Rules and Cases in Law: Resources for Aligning Learning and Reasoning in Structured Domains. Argument & Computation – Volume 14, 235-243. Amsterdam: IOS Press. PDF
Steging, C., Renooij, S., & Verheij, B. (2022). Discovering the Rationale of Decisions. In HHAI2022: Augmenting Human Intellect (pp. 255-257). IOS Press. PDF
Steging, C., Renooij, S., & Verheij, B. (2021). Rationale Discovery and Explainable AI. Legal Knowledge and Information Systems. JURIX 2021: The Thirty-fourth Annual Conference (ed. Schweighofer, E.), 225-234. Amsterdam: IOS Press. PDF
Steging, C., Renooij, S., & Verheij, B. (2021). Discovering the Rationale of Decisions: Towards a Method for Aligning Learning and Reasoning. The 18th International Conference on Artificial Intelligence and Law (ICAIL 2021). Proceedings of the Conference, 235-239. New York (New York): ACM. PDF
Steging C., Renooij S., Verheij, B.. Discovering the Rationale of Decisions: Experiments on Aligning Learning and Reasoning. In: 4th EXplainable AI in Law Workshop (XAILA 2021). ACM; 2021. PDF
Steging, C., Schomaker, L.R.B., & Verheij, B. (2019). The XAI Paradox: systems that perform well for the wrong reasons (abstract). BNAIC/BENELEARN 2019. Proceedings of the 31st Benelux Conference on Artificial Intelligence (BNAIC 2019) and the 28th Belgian Dutch Conference on Machine Learning (Benelearn 2019). Brussels, Belgium, November 6-8, 2019 (eds. Beuls, K. , Bogaerts, B., Bontempi, G., Geurts, P., Harley, N., Lebichot, B., Lenaerts, T., Louppe, G., & Van Eecke, P.). CEUR Workshop Proceedings. PDF