Carmen Mazijn — accepted AI-conference papers

2025

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 2025findings

Citation practices are crucial in shaping the structure of scientific knowledge, yet they are often influenced by contemporary norms and biases. The emergence of Large Language Models (LLMs) introduces a new dynamic to these practices. Interestingly, the characteristics and potential biases of refer…

Cited by 21 Source ↗PDF ↗code ↗Scholar ↗

2023

LUCID: Exposing Algorithmic Bias through Inverse Design

Carmen Mazijn, Carina Prunkl, Andres Algaba, Jan Danckaert, Vincent Ginis

AAAI 2023technical

AI systems can create, propagate, support, and automate bias in decision-making processes. To mitigate biased decisions, we both need to understand the origin of the bias and define what it means for an algorithm to make fair decisions. Most group fairness notions assess a model's equality of outcom…

Cited by 3 Source ↗PDF ↗Scholar ↗