arxiv
PublishedJune 2, 2026 at 4:00 AM
Calibrating Uncertainty for Zero-Shot Adversarial CLIP
Publisher summary· verbatim
arXiv:2512.12997v2 Announce Type: replace-cross Abstract: CLIP delivers strong zero-shot classification but remains highly vulnerable to adversarial attacks. Prior adversarial fine-tuning work primarily matches predicted logits between clean and adversarial examples, which overlooks uncertainty cali
Stay posted· Newsletter
A 5-min weekly brief — top movers, price watch, story of the week.
Discussion
No replies yet. Be first.
Related coverage
More from ARXIV
arxivSFMambaNet: Spectral-Frequency Enhanced Selective State Space Model for Correspondence Pruning15harxivOptical-Guided Neural Collapse for SAR Few-Shot Class Incremental Learning15harxivDynamic Infilling Anchors for Format-Constrained Generation in Diffusion Large Language Models15hThe Bubble Brief
WEEKLYRead AI insights every Tuesday — top movers, new releases, story of the week.
Originally published on arxiv ↗