42 citations · 266 across the 59 of their papers we have counts for
5 papers · 2 filters
Choosing the right basis for interpretability: Psychophysical comparison between neuron-based and dictionary-based representations
Julien Colin, Lore Goetschalckx, Thomas Fel +3
Interpretability research often adopts a neuron-centric lens, treating individual neurons as the fundamental units of explanation. However, neuron-level explanations can be undermi…
Understanding Visual Feature Reliance through the Lens of Complexity
Thomas Fel, Louis Bethune, Andrew Kyle Lampinen +2
Recent studies suggest that deep learning models inductive bias towards favoring simpler features may be one of the sources of shortcut learning. Yet, there has been limited focus…
Beyond the Doors of Perception: Vision Transformers Represent Relations Between Objects
Michael A. Lepori, Alexa R. Tartaglini, Wai Keen Vong +3
Though vision transformers (ViTs) have achieved state-of-the-art performance in a variety of settings, they exhibit surprising failures when performing tasks involving visual relat…
Latent Representation Matters: Human-like Sketches in One-shot Drawing Tasks
Victor Boutin, Rishav Mukherji, Aditya Agrawal +4
Humans can effortlessly draw new categories from a single exemplar, a feat that has long posed a challenge for generative models. However, this gap has started to close with recent…
The 3D-PC: a benchmark for visual perspective taking in humans and machines
Drew Linsley, Peisen Zhou, Alekh Karkada Ashok +5
Visual perspective taking (VPT) is the ability to perceive and reason about the perspectives of others. It is an essential feature of human intelligence, which develops over the fi…