4 papers
SpurCon: Weighted Supervised Contrastive Learning for Mitigating Spurious Cues in Medical Imaging
Shenhav Nadir, Meir Yossef Levi, Eyal Gofer +1
Despite the rapid progress of deep neural networks in visual recognition, their adoption in high-risk medical applications remains limited due to reliability and robustness concern…
A Classifier-Agnostic Zero-Shot Adversarial Attack Detection via CLIP
Hodaya Krakover, Meir Yossef Levi, Eyal Gofer +1
Adversarial attacks pose a challenge to the reliability of deep learning models, motivating effective detection methods. Existing techniques often rely on attack-specific assumptio…
Whitened CLIP as a Likelihood Surrogate of Images and Captions
Roy Betser, Meir Yossef Levi, Guy Gilboa
Likelihood approximations for images are not trivial to compute and can be useful in many applications. We examine the use of Contrastive Language-Image Pre-training (CLIP) to asse…
The Double-Ellipsoid Geometry of CLIP
Meir Yossef Levi, Guy Gilboa
Contrastive Language-Image Pre-Training (CLIP) is highly instrumental in machine learning applications within a large variety of domains. We investigate the geometry of this embedd…