We show that interval estimation based methods produce better distilled embedders in multi-teacher distillation settings compared to MSE or Cosine base methods.

We propose CLIPTTA, a contrastive test-time adaptation method for CLIP that improves both accuracy and OOD detection in closed- and open-set settings.