LUCID: Exposing Algorithmic Bias through Inverse Design. - Carmen Mazijn; Carina Prunkl; Andres Algaba; Jan Danckaert; Vincent Ginis (AAAI, 2023)

LUCID-GAN: Conditional Generative Models to Locate Unfairness. - Andres Algaba; Carmen Mazijn; Carina Prunkl; Jan Danckaert; Vincent Ginis (xAI (3), 2023)

Dataset Artefacts are the Hidden Drivers of the Declining Disruptiveness in Science. - Vincent Holst; Andres Algaba; Floriano Tori; Sylvia Wenmackers; Vincent Ginis (CoRR, 2024)

Large Language Models Reflect Human Citation Patterns with a Heightened Citation Bias. - Andres Algaba; Carmen Mazijn; Vincent Holst; Floriano Tori; Sylvia Wenmackers; Vincent Ginis (NAACL (Findings), 2025)

The Relationship Between Reasoning and Performance in Large Language Models - o3 (mini) Thinks Harder, Not Longer. - Marthe Ballon; Andres Algaba; Vincent Ginis (CoRR, 2025)

Flexible Counterfactual Explanations with Generative Models. - Stig Hellemans; Andres Algaba; Sam Verboven; Vincent Ginis (CoRR, 2025)

How Deep Do Large Language Models Internalize Scientific Literature and Citation Practices? - Andres Algaba; Vincent Holst; Floriano Tori; Melika Mobini; Brecht Verbeken; Sylvia Wenmackers; Vincent Ginis (CoRR, 2025)

Decision-centric fairness: Evaluation and optimization for resource allocation problems. - Simon De Vos; Jente Van Belle; Andres Algaba; Wouter Verbeke; Sam Verboven (CoRR, 2025)