As the performance and complexity of machine learning models have grown significantly
over the last years, there has been an increasing need to develop methodologies to …

Despite the impressive performance of Artificial Intelligence (AI) systems, their robustness
remains elusive and constitutes a key issue that impedes large-scale adoption. Besides …

Generative models are increasingly being used in various applications, such as text
generation, commonsense reasoning, and question-answering. To be effective globally …

Existing research in measuring and mitigating gender bias predominantly centers on
English, overlooking the intricate challenges posed by non-English languages and the …

Abstract Concepts are an important construct in semantics, based on which humans
understand the world with various levels of abstraction. With the recent advances in …

With recent advances in explainable artificial intelligence (XAI), researchers have started to
pay attention to concept-level explanations, which explain model predictions with a high …

Recent developments in explainable AI (XAI) aim to improve the transparency of black-box
models. However, empirically evaluating the interpretability of these XAI techniques is still …

Pilot studies are an essential cornerstone of the design of crowdsourcing campaigns, yet
they are often only mentioned in passing in the scholarly literature. A lack of details …

Work on value alignment aims to ensure that human values are respected by AI systems.
However, existing approaches tend to rely on universal framings of human values that …

In the shift towards human-centered manufacturing, our two-year longitudinal study
investigates the real-world impact of deploying Cognitive Assistants (CAs) in factories. The …