activity
20172023
most citedBadNL: Backdoor Attacks against NLP Models with Semantic-preserving Improvements

190 citations · 222 across the 13 of their papers we have counts for

collaborators

13 papers

eess.IV2023★ 6 cited

SHISRCNet: Super-resolution And Classification Network For Low-resolution Breast Cancer Histopathology Image

Luyuan Xie, Cong Li, Zirui Wang +4

The rapid identification and accurate diagnosis of breast cancer, known as the killer of women, have become greatly significant for those patients. Numerous breast cancer histopath…

cs.MM2023★ 2 cited

Building a Modal-balanced BlockChain with Semantic Reconstruction

Zhijie Tan, Xiang Yuan, Shengwei Meng +4

The current large blockchain systems (BTC Lightning network, Ethereum, etc.) are generally facing the problems of low persistence rates and high storage costs. Therefore, users ten…

cs.CR2023

NCL: Textual Backdoor Defense Using Noise-augmented Contrastive Learning

Shengfang Zhai, Qingni Shen, Xiaoyi Chen +4

At present, backdoor attacks attract attention as they do great harm to deep learning models. The adversary poisons the training data making the model being injected with a backdoo…

cs.CL2022

Apple of Sodom: Hidden Backdoors in Superior Sentence Embeddings via Contrastive Learning

Xiaoyi Chen, Baisong Xin, Shengfang Zhai +3

This paper finds that contrastive learning can produce superior sentence embeddings for pre-trained models but is also vulnerable to backdoor attacks. We present the first backdoor…

cs.SD2022

TC-SKNet with GridMask for Low-complexity Classification of Acoustic scene

Luyuan Xie, Yan Zhong, Lin Yang +3

Convolution neural networks (CNNs) have good performance in low-complexity classification tasks such as acoustic scene classifications (ASCs). However, there are few studies on the…

cs.CR2022

Kallima: A Clean-label Framework for Textual Backdoor Attacks

Xiaoyi Chen, Yinpeng Dong, Zeyu Sun +3

Although Deep Neural Network (DNN) has led to unprecedented progress in various natural language processing (NLP) tasks, research shows that deep models are extremely vulnerable to…