Capability not equal to Interpretability: Human Interpretability of Vision Foundation Models
Researchers developed a framework using psychophysics protocols to measure human interpretability in vision models. They tested six vision transformers, finding that foundation models are consistently less interpretable than supervised counterparts. Interpretability is not linked to downstream performance, but rather correlates with the locality of feature activations and coarse-grained semantic alignment with human perception.