no code implementations • 12 Feb 2024 • Haoyu Wang, Guozheng Ma, Ziqiao Meng, Zeyu Qin, Li Shen, Zhong Zhang, Bingzhe Wu, Liu Liu, Yatao Bian, Tingyang Xu, Xueqian Wang, Peilin Zhao
To further exploit the capabilities of bootstrapping, we investigate and adjust the training order of data, which yields improved performance of the model.
1 code implementation • 11 Oct 2023 • Liang Chen, Yang Deng, Yatao Bian, Zeyu Qin, Bingzhe Wu, Tat-Seng Chua, Kam-Fai Wong
Large language models (LLMs) outperform information retrieval techniques for downstream knowledge-intensive tasks when being prompted to generate world knowledge.
1 code implementation • NeurIPS 2023 • Rui Min, Zeyu Qin, Li Shen, Minhao Cheng
Our analysis shows that with the low poisoning rate, the entanglement between backdoor and clean features undermines the effect of tuning-based defenses.
1 code implementation • 3 Feb 2023 • Zeyu Qin, Liuyi Yao, Daoyuan Chen, Yaliang Li, Bolin Ding, Minhao Cheng
We conduct the first study of backdoor attacks in the pFL framework, testing 4 widely used backdoor attacks against 6 pFL methods on benchmark datasets FEMNIST and CIFAR-10, a total of 600 experiments.
3 code implementations • 12 Oct 2022 • Zeyu Qin, Yanbo Fan, Yi Liu, Li Shen, Yong Zhang, Jue Wang, Baoyuan Wu
Furthermore, RAP can be naturally combined with many existing black-box attack techniques, to further boost the transferability.
1 code implementation • 2 Oct 2022 • Jiancong Xiao, Zeyu Qin, Yanbo Fan, Baoyuan Wu, Jue Wang, Zhi-Quan Luo
Therefore, adversarial training for multiple perturbations (ATMP) is proposed to generalize the adversarial robustness over different perturbation types (in $\ell_1$, $\ell_2$, and $\ell_\infty$ norm-bounded perturbations).
no code implementations • 8 Feb 2022 • Peiying Zhang, Chao Wang, Zeyu Qin, Haotong Cao
Network virtualization technology is a promising technology to support IoD, so the allocation of virtual resources becomes a crucial issue in IoD.
1 code implementation • NeurIPS 2021 • Zeyu Qin, Yanbo Fan, Hongyuan Zha, Baoyuan Wu
We conduct the theoretical analysis about the effectiveness of RND against query-based black-box attacks and the corresponding adaptive attacks.