Xianglong Liu

Patch-wise Attack for Fooling Deep Neural Network

2020 · arXiv (Cornell University)

By adding human-imperceptible noise to clean images, the resultant adversarial examples can fool other unknown models. Features of a pixel extracted by deep neural networks (DNNs) are influenced by its surrounding regions, and different DNNs …

Vision-fused Attack: Advancing Aggressive and Stealthy Adversarial Text against Neural Machine Translation

2024 · arXiv (Cornell University)

While neural machine translation (NMT) models achieve success in our daily lives, they show vulnerability to adversarial attacks. Despite being harmful, these attacks also offer benefits for interpreting and enhancing NMT models, thus drawing increased …