Joel Valdivia Ortega

Randomized-MLP Regularization Improves Domain Adaptation and Interpretability in DINOv2

Vision Transformers (ViTs), such as DINOv2, achieve strong performance across domains but often repurpose low-informative patch tokens in ways that reduce the interpretability of attention and feature maps. This challenge is especially evident in medical imaging, where domain shifts can degrade both…