1 code implementation • 18 Apr 2023 • Xiaomei Zhang, Zhaoxi Zhang, Qi Zhong, Xufei Zheng, Yanjun Zhang, Shengshan Hu, Leo Yu Zhang
To explore how to use the masked language model in adversarial detection, we propose a novel textual adversarial example detection method, namely Masked Language Model-based Detection (MLMD), which can produce clearly distinguishable signals between normal examples and adversarial examples by exploring the changes in manifolds induced by the masked language model.
1 code implementation • 14 May 2022 • Zhaoxi Zhang, Leo Yu Zhang, Xufei Zheng, Bilal Hussain Abbasi, Shengshan Hu
The usage of deep learning is being escalated in many applications.
no code implementations • NeurIPS 2021 • Zhaoxi Zhang, Leo Yu Zhang, Xufei Zheng, Jinyu Tian, Jiantao Zhou
To alleviate this problem, we explore how to detect adversarial examples with disentangled label/semantic features under the autoencoder structure.