4 papers
Reasoning Models Don't Just Think Longer, They Move Differently
Anders Gjølbye, Lars Kai Hansen, Sanmi Koyejo
Reasoning-trained language models often spend more tokens on harder problems, but longer chains of thought do not show whether a model is merely computing for more steps or followi…
Large Vision Models Can Solve Mental Rotation Problems
Sebastian Ray Mason, Anders Gjølbye, Phillip Chavarria Højbjerg +2
Mental rotation is a key test of spatial reasoning in humans and has been central to understanding how perception supports cognition. Despite the success of modern vision transform…
Challenges in explaining deep learning models for data with biological variation
Lenka Tětková, Erik Schou Dreier, Robin Malm +1
Much machine learning research progress is based on developing models and evaluating them on a benchmark dataset (e.g., ImageNet for images). However, applying such benchmark-succe…
Knowledge graphs for empirical concept retrieval
Lenka Tětková, Teresa Karen Scheidt, Maria Mandrup Fogh +3
Concept-based explainable AI is promising as a tool to improve the understanding of complex models at the premises of a given user, viz.\ as a tool for personalized explainability.…