21 citations · 24 across the 5 of their papers we have counts for
5 papers
Backdoor Attacks on Pre-trained Models by Layerwise Weight Poisoning
Linyang Li, Demin Song, Xiaonan Li +3
\textbf{P}re-\textbf{T}rained \textbf{M}odel\textbf{s} have been widely applied and recently proved vulnerable under backdoor attacks: the released pre-trained weights can be malic…
Searching for an Effective Defender: Benchmarking Defense against Adversarial Word Substitution
Zongyi Li, Jianhan Xu, Jiehang Zeng +5
Recent studies have shown that deep neural networks are vulnerable to intentionally crafted adversarial examples, and various methods have been proposed to defend against adversari…
Certified Robustness to Text Adversarial Attacks by Randomized [MASK]
Jiehang Zeng, Xiaoqing Zheng, Jianhan Xu +3
Recently, few certified defense methods have been developed to provably guarantee the robustness of a text classifier to adversarial synonym substitutions. However, all existing ce…
SparseGAN: Sparse Generative Adversarial Network for Text Generation
Liping Yuan, Jiehang Zeng, Xiaoqing Zheng
It is still a challenging task to learn a neural text generation model under the framework of generative adversarial networks (GANs) since the entire training process is not differ…
Learning Structured Embeddings of Knowledge Graphs with Adversarial Learning Framework
Jiehang Zeng, Lu Liu, Xiaoqing Zheng
Many large-scale knowledge graphs are now available and ready to provide semantically structured information that is regarded as an important resource for question answering and de…