3 papers
cs.LG2025
Towards Safeguarding LLM Fine-tuning APIs against Cipher Attacks
Jack Youstra, Mohammed Mahfoud, Yang Yan +3
Large language model fine-tuning APIs enable widespread model customization, yet pose significant safety risks. Recent work shows that adversaries can exploit access to these APIs…
cs.LG2025
Data-Free Universal Attack by Exploiting the Intrinsic Vulnerability of Deep Models
YangTian Yan, Jinyu Tian
Deep neural networks (DNNs) are susceptible to Universal Adversarial Perturbations (UAPs), which are instance agnostic perturbations that can deceive a target model across a wide r…
cs.CV2025
IOL-Net: Intra-Inter Objectness Learning Network for Point-Supervised X-Ray Prohibited Item Detection
Sanjoeng Wong, Yan Yan
Automatic detection of prohibited items in X-ray images plays a crucial role in public security. However, existing methods rely heavily on labor-intensive box annotations. To addre…