Enhancing the Transferability of Adversarial Examples via a Few Queries. - Xiangyuan Yang; Jie Lin 002; Hanlin Zhang 001; Xinyu Yang 001; Peng Zhao 001 (CoRR, 2022)

Mask-Guided Divergence Loss Improves the Generalization and Robustness of Deep Neural Network. - Xiangyuan Yang; Jie Lin 002; Hanlin Zhang 001; Xinyu Yang 001; Peng Zhao 001 (CoRR, 2022)

FACM: Correct the Output of Deep Neural Network with Middle Layers Features against Adversarial Samples. - Xiangyuan Yang; Jie Lin 002; Hanlin Zhang 001; Xinyu Yang 001; Peng Zhao 001 (CoRR, 2022)

A Multi-Stage Triple-Path Method For Speech Separation in Noisy and Reverberant Environments. - Zhaoxi Mu; Xinyu Yang; Xiangyuan Yang; Wenjing Zhu (ICASSP, 2023)

Fuzziness-tuned: Improving the Transferability of Adversarial Examples. - Xiangyuan Yang; Jie Lin 002; Hanlin Zhang 001; Xinyu Yang 001; Peng Zhao 001 (CoRR, 2023)

Improving the transferability of adversarial examples via direction tuning. - Xiangyuan Yang; Jie Lin 002; Hanlin Zhang 001; Xinyu Yang 001; Peng Zhao 001 (Inf. Sci., 2023)

An auxiliary correction model implemented by the Correction Property of intermediate layer against adversarial examples. - Xiangyuan Yang; Jie Lin 002; Hanlin Zhang 001; Xinyu Yang 001; Peng Zhao 001 (Appl. Soft Comput., 2024)

Adversarial Detection with a Dynamically Stable System. - Xiaowei Long; Jie Lin 002; Xiangyuan Yang (CoRR, 2024)

Object Style Diffusion for Generalized Object Detection in Urban Scene. - Hao Li 025; Xiangyuan Yang; Mengzhu Wang; Long Lan; Ke Liang 006; Xinwang Liu 002; Kenli Li 001 (CoRR, 2024)

Improving query efficiency of black-box attacks via the preference of deep learning models. - Xiangyuan Yang; Jie Lin 002; Hanlin Zhang 001; Peng Zhao 001 (Inf. Sci., 2024)

Enhancing adversarial transferability via transformation inference. - Jiaxin Hu; Jie Lin 002; Xiangyuan Yang; Hanlin Zhang 001; Peng Zhao 001 (Neural Networks, 2025)

Rethinking the optimization objective for transferable adversarial examples from a fuzzy perspective. - Xiangyuan Yang; Jie Lin 002; Hanlin Zhang 001; Peng Zhao 001 (Neural Networks, 2025)