3 papers
cs.CV2025
High-Quality Proposal Encoding and Cascade Denoising for Imaginary Supervised Object Detection
Zhiyuan Chen, Yuelin Guo, Zitong Huang +3
Object detection models demand large-scale annotated datasets, which are costly and labor-intensive to create. This motivated Imaginary Supervised Object Detection (ISOD), where mo…
cs.LG2025
Membership Inference Attack with Partial Features
Xurun Wang, Guangrui Liu, Xinjie Li +4
Machine learning models are vulnerable to membership inference attack, which can be used to determine whether a given sample appears in the training data. Most existing methods ass…
cs.LG2025
Circumventing Backdoor Space via Weight Symmetry
Jie Peng, Hongwei Yang, Jing Zhao +4
Deep neural networks are vulnerable to backdoor attacks, where malicious behaviors are implanted during training. While existing defenses can effectively purify compromised models,…