3 papers
cs.CV2026
From Interpretability Methods to Interpretable Models
Julien Colin, Nuria Oliver, Thomas Serre
More than a decade in, explainable AI (XAI) for computer vision has assembled a mature toolbox: attribution, feature visualization, concept-based, and circuit-based methods. Yet al…
cs.CV2026
Capability Interpretability: Human Interpretability of Vision Foundation Models
Julien Colin, Lore Goetschalckx, Nuria Oliver +1
How interpretable are the features of leading vision models? The question is increasingly pressing as these models move from research benchmarks into high-stakes deployments, yet e…
cs.CV2024
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…