We introduce the concept of an-semimetric that satisfies the same axioms as a topological
metric, except for an arbitrarily small allowance to violate the triangle inequality. Under this …

Researchers have shown that deep learning models are susceptible to adversarial
examples, however, most existing works focus on supervised learning. Recently, research …

Adversarial example detection, which can be conveniently applied in many scenarios, is
important in the area of adversarial defense. Unfortunately, existing detection methods suffer …

Deep neural networks (DNNs) have been applied in many computer vision tasks and
achieved state-of-the-art (SOTA) performance. However, misclassification will occur when …

Data poisoning attacks on clustering algorithms have received limited attention, with existing
methods struggling to scale efficiently as dataset sizes and feature counts increase. These …

Compositional Zero-shot Learning (CZSL) aims to identify novel compositions via known
attribute-object pairs. The primary challenge in CZSL tasks lies in the significant …