Search Results for author: Haoran Lyu

Found 5 papers, 2 papers with code

Artificial Intelligence Security Competition (AISC)

no code implementations • 7 Dec 2022 • Yinpeng Dong, Peng Chen, Senyou Deng, Lianji L, Yi Sun, Hanyu Zhao, Jiaxing Li, Yunteng Tan, Xinyu Liu, Yangyi Dong, Enhui Xu, Jincai Xu, Shu Xu, Xuelin Fu, Changfeng Sun, Haoliang Han, Xuchong Zhang, Shen Chen, Zhimin Sun, Junyi Cao, Taiping Yao, Shouhong Ding, Yu Wu, Jian Lin, Tianpeng Wu, Ye Wang, Yu Fu, Lin Feng, Kangkang Gao, Zeyu Liu, Yuanzhe Pang, Chengqi Duan, Huipeng Zhou, Yajie Wang, Yuhang Zhao, Shangbo Wu, Haoran Lyu, Zhiyu Lin, YiFei Gao, Shuang Li, Haonan Wang, Jitao Sang, Chen Ma, Junhao Zheng, Yijia Li, Chao Shen, Chenhao Lin, Zhichao Cui, Guoshuai Liu, Huafeng Shi, Kun Hu, Mengxin Zhang

The security of artificial intelligence (AI) is an important research area towards safe, reliable, and trustworthy AI systems.

Autonomous Driving Face Recognition +1

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FIMP: Foundation Model-Informed Message Passing for Graph Neural Networks

no code implementations • 17 Oct 2022 • Syed Asad Rizvi, Nhi Nguyen, Haoran Lyu, Benjamin Christensen, Josue Ortega Caro, Antonio H. O. Fonseca, Emanuele Zappala, Maryam Bagherian, Christopher Averill, Chadi G. Abdallah, Amin Karbasi, Rex Ying, Maria Brbic, Rahul Madhav Dhodapkar, David van Dijk

Foundation models have revolutionized the landscape of Deep Learning (DL), serving as a versatile platform which can be adapted to a wide range of downstream tasks.

Benchmarking Representation Learning

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Improving the Transferability of Adversarial Examples with Restructure Embedded Patches

1 code implementation • 27 Apr 2022 • Huipeng Zhou, Yu-an Tan, Yajie Wang, Haoran Lyu, Shangbo Wu, Yuanzhang Li

We attack the unique self-attention mechanism in ViTs by restructuring the embedded patches of the input.

Specificity

132

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Code

Boosting Adversarial Transferability of MLP-Mixer

no code implementations • 26 Apr 2022 • Haoran Lyu, Yajie Wang, Yu-an Tan, Huipeng Zhou, Yuhang Zhao, Quanxin Zhang

Our method can mask the part input of the Mixer layer, avoid overfitting of the adversarial examples to the source model, and improve the transferability of cross-architecture.

Adversarial Attack

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Unrestricted Adversarial Attacks on ImageNet Competition

1 code implementation • 17 Oct 2021 • Yuefeng Chen, Xiaofeng Mao, Yuan He, Hui Xue, Chao Li, Yinpeng Dong, Qi-An Fu, Xiao Yang, Tianyu Pang, Hang Su, Jun Zhu, Fangcheng Liu, Chao Zhang, Hongyang Zhang, Yichi Zhang, Shilong Liu, Chang Liu, Wenzhao Xiang, Yajie Wang, Huipeng Zhou, Haoran Lyu, Yidan Xu, Zixuan Xu, Taoyu Zhu, Wenjun Li, Xianfeng Gao, Guoqiu Wang, Huanqian Yan, Ying Guo, Chaoning Zhang, Zheng Fang, Yang Wang, Bingyang Fu, Yunfei Zheng, Yekui Wang, Haorong Luo, Zhen Yang

Many works have investigated the adversarial attacks or defenses under the settings where a bounded and imperceptible perturbation can be added to the input.

Adversarial Attack

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