Every month, we want to acknowledge some valuable TAILOR papers, selected among the papers published by scientists belonging to our network by TAILOR principal investigator Fredrik Heintz. The list of the most valuable papers gathers contributions from different TAILOR partners, each providing valuable insights on different topics related to TrustworthyAI. This is the very last […]
TAILOR Selected papers: November 2024 Read More »
Every month, we want to acknowledge some valuable TAILOR papers, selected among the papers published by scientists belonging to our network by TAILOR principal investigator Fredrik Heintz.The list of the most valuable papers gathers contributions from different TAILOR partners, each providing valuable insights on different topics related to TrustworthyAI.Stay tuned for other valuable insights and
TAILOR Selected papers: October 2024 Read More »
Every month, we want to acknowledge some valuable TAILOR papers, selected among the papers published by scientists belonging to our network by TAILOR principal investigator Fredrik Heintz.The list of the most valuable papers gathers contributions from different TAILOR partners, each providing valuable insights on different topics related to TrustworthyAI.Stay tuned for other valuable insights and
TAILOR Selected papers: September 2024 Read More »
Sietze Kai Kuilman PhD at Delft University of Technology Quite recently many large Tech companies have proffered the idea of an Advanced AI Assistant. These assistants should supposedly be able to all manner of tasks for us. They may be able to arrange flight tickets for us, book hotels, order groceries, and plan our agenda’s.
Meaningful Human Control and Advanced AI Assistants Read More »
Antonio G. Marques Professor at King Juan Carlos University Graphs are ubiquitous for modeling the irregular (non-Euclidean) structure of complex data. However, real-world scenarios often involve relationships that span several nodes. While hypergraphs can address such complexities, they lack the mathematical tractability and theoretical foundation of simple graphs. Our strategy for managing these intricate relationships
Learning the structure of complex datasets: The case for simplicial complexes Read More »
IRT-SystemX is a public institute for industrial maturation and transfer, with a long collaboration history with TAILOR partner #3 Inria. IRT-SystemX, together with several academic (including Inria TAU) and industrial (including NVIDIA, RTE and Criteo) partners, organized these Data Challenges to promote the use of Machine Learning-based surrogate models to numerically solve physical problems, through
Machine Learning for Physical Simulations Read More »
The 4th TAILOR Summer School on Artificial Intelligence was held in Athens, Greece, from July 15 to 26, 2024. The summer school was held at the same time and had an identical program with the 2nd European Summer School on AI (ESSAI) and the 21st Advanced Course on Artificial Intelligence (ACAI). The Program Chairs of
Report from the 4th TAILOR Summer School Read More »
Every month, we want to acknowledge some valuable TAILOR papers, selected among the papers published by scientists belonging to our network by TAILOR principal investigator Fredrik Heintz.The list of the most valuable papers gathers contributions from different TAILOR partners, each providing valuable insights on different topics related to TrustworthyAI.Stay tuned for other valuable insights and
TAILOR Selected papers: August 2024 Read More »
Tiffany Matej Hrkalovic PhD Student at Vrije University Amsterdam & Delft University of Technology The enigma of human willingness and ability to cooperate has been a topic of interest for millennia. However, due to the recent technological developments in designing intelligent systems and their potential usage in cooperative settings with humans, newer research is steered
Lea Krause PhD candidate at Vrije Universiteit Amsterdam The project addresses the critical need for cultural diversity in multilingual datasets used to train and evaluate language models and conversational agents. Current practices often involve translating English-centric content, which limits the cultural authenticity and applicability of these datasets across different regions. For example, evaluating models using
Exploring the (Lack of) Cultural Diversity in Multilingual Datasets for NLP Read More »
