1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.CL2025
Soft Token Attacks Cannot Reliably Audit Unlearning in Large Language Models
Haokun Chen, Sebastian Szyller, Weilin Xu +1
Large language models (LLMs) are trained using massive datasets, which often contain undesirable content such as harmful texts, personal information, and copyrighted material. To a…
cs.CV2024
Imperceptible Adversarial Examples in the Physical World
Weilin Xu, Sebastian Szyller, Cory Cornelius +5
Adversarial examples in the digital domain against deep learning-based computer vision models allow for perturbations that are imperceptible to human eyes. However, producing simil…
cs.CV2024★ 1 cited
Investigating the Semantic Robustness of CLIP-based Zero-Shot Anomaly Segmentation
Kevin Stangl, Marius Arvinte, Weilin Xu +1
Zero-shot anomaly segmentation using pre-trained foundation models is a promising approach that enables effective algorithms without expensive, domain-specific training or fine-tun…