7 citations · 7 across the 5 of their papers we have counts for
5 papers
Decomposing Factual Sycophancy in Language Models: How Size and Instruction Tuning Shape Robustness
Victor De Marez, Luna De Bruyne, Walter Daelemans
Factual sycophancy occurs when a language model abandons a correct, verifiable answer under social pressure. Because a flip occurs only when pressure toward a false answer exceeds…
An Agentic AI Framework for Training General Practitioner Student Skills
Victor De Marez, Jens Van Nooten, Luna De Bruyne +1
Advancements in large language models offer strong potential for enhancing virtual simulated patients (VSPs) in medical education by providing scalable alternatives to resource-int…
Gender Bias in English-to-Greek Machine Translation
Eleni Gkovedarou, Joke Daems, Luna De Bruyne
As the demand for inclusive language increases, concern has grown over the susceptibility of machine translation (MT) systems to reinforce gender stereotypes. This study investigat…
WinoWhat: A Parallel Corpus of Paraphrased WinoGrande Sentences with Common Sense Categorization
Ine Gevers, Victor De Marez, Luna De Bruyne +1
In this study, we take a closer look at how Winograd schema challenges can be used to evaluate common sense reasoning in LLMs. Specifically, we evaluate generative models of differ…
Joint Emotion Label Space Modelling for Affect Lexica
Luna De Bruyne, Pepa Atanasova, Isabelle Augenstein
Emotion lexica are commonly used resources to combat data poverty in automatic emotion detection. However, vocabulary coverage issues, differences in construction method and discre…