Publications

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2023

Semantic Adversarial Attacks via Diffusion Models

Chenan Wang, Jinhao Duan, Chaowei Xiao, Edward Kim, Matthew Stamm, Kaidi Xu

Improve Video Representation with Temporal Adversarial Augmentation

Jinhao Duan, Quanfu Fan, Hao Cheng, Xiaoshuang Shi, Kaidi Xu

Real-Time Robust Video Object Detection System Against Physical-World Adversarial Attacks

Husheng Han, Xing Hu, Yifan Hao, Kaidi Xu, Pucheng Dang, Ying Wang, Yongwei Zhao, Zidong Du, Qi Guo, Yanzhi Wang, Xishan Zhang, Tianshi Chen

Are diffusion models vulnerable to membership inference attacks?

Jinhao Duan, Fei Kong, Shiqi Wang, Xiaoshuang Shi, Kaidi Xu

Shifting attention to relevance: Towards the uncertainty estimation of large language models

Jinhao Duan, Hao Cheng, Shiqi Wang, Chenan Wang, Alex Zavalny, Renjing Xu, Bhavya Kailkhura, Kaidi Xu

An Efficient Membership Inference Attack for the Diffusion Model by Proximal Initialization

Fei Kong, Jinhao Duan, RuiPeng Ma, Hengtao Shen, Xiaofeng Zhu, Xiaoshuang Shi, Kaidi Xu

2022

General cutting planes for bound-propagation-based neural network verification

Huan Zhang*, Shiqi Wang*, Kaidi Xu*, Linyi Li, Bo Li, Suman Jana, Cho-Jui Hsieh, J Zico Kolter

Toward robust spiking neural network against adversarial perturbation

Ling Liang, Kaidi Xu, Xing Hu, Lei Deng, Yuan Xie

A Branch and Bound Framework for Stronger Adversarial Attacks of ReLU Networks

Huan Zhang, Shiqi Wang, Kaidi Xu, Yihan Wang, Suman Jana, Cho-Jui Hsieh, Zico Kolter

2021

Beta-CROWN: Efficient Bound Propagation with Per-neuron Split Constraints for Neural Network Robustness Verification

Shiqi Wang*, Huan Zhang*, Kaidi Xu*, Xue Lin, Suman Jana, Cho-Jui Hsieh, J Zico Kolter

ScaleCert: Scalable Certified Defense against Adversarial Patches with Sparse Superficial Layers

Husheng Han*, Kaidi Xu*, Xing Hu, Xiaobing Chen, Ling Liang, Zidong Du, Qi Guo, Yanzhi Wang, Yunji Chen

Fast and Complete: Enabling Complete Neural Network Verification with Rapid and Massively Parallel Incomplete Verifiers

Kaidi Xu*, Huan Zhang*, Shiqi Wang, Yihan Wang, Suman Jana, Xue Lin, Cho-Jui Hsieh

On Fast Adversarial Robustness Adaptation in Model-Agnostic Meta-Learning

Ren Wang, Kaidi Xu, Sijia Liu, Pin-Yu Chen, Tsui-Wei Weng, Chuang Gan, Meng Wang

Loss-based Attention for Interpreting Image-level Prediction of Convolutional Neural Networks

Xiaoshuang Shi, Fuyong Xing, Kaidi Xu, Pingjun Chen, Yun Liang, Zhiyong Lu, Zhenhua Guo

2020

Automatic Perturbation Analysis for Scalable Certified Robustness and Beyond

Kaidi Xu*, Zhouxing Shi*, Huan Zhang*, Yihan Wang, Kai-Wei Chang, Minlie Huang, Bhavya Kailkhura, Xue Lin, Cho-Jui Hsieh

Zeroth-Order Hybrid Gradient Descent: Towards A Principled Black-Box Optimization Framework

Pranay Sharma, Kaidi Xu, Sijia Liu, Pin-Yu Chen, Xue Lin, Pramod K. Varshney.

Adversarial T-shirt! Evading Person Detectors in A Physical World

Kaidi Xu, Gaoyuan Zhang, Sijia Liu, Quanfu Fan, Mengshu Sun, Hongge Chen, Pin-Yu Chen, Yanzhi Wang, Xue Lin

Min-Max Optimization without Gradients: Convergence and Applications to Black-Box Evasion and Poisoning Attacks

Sijia Liu*, Songtao Lu*, Xiangyi Chen*, Yao Feng*, Kaidi Xu*, Abdullah Al-Dujaili, Minyi Hong, Una-May O’Reilly

Light-weight Calibrator: a Separable Component for Unsupervised Domain Adaptation

Shaokai Ye, Kailu Wu, Mu Zhou, Yunfei Yang, Kaidi Xu, Jiebo Song, Aojun Zhou, Chenglong Bao, Kaisheng Ma

Towards an Efficient and General Framework of Robust Training for Graph Neural Networks

Kaidi Xu, Sijia Liu, Pin-Yu Chen, Mengshu Sun, Caiwen Ding, Bhavya Kailkhura, Xue Lin

2019

ZO-AdaMM: Zeroth-Order Adaptive Momentum Method for Black-Box Optimization

Xiangyi Chen*, Sijia Liu*, Kaidi Xu*, Xingguo Li, Xue Lin, Mingyi Hong, David Cox

Adversarial Robustness vs Model Compression, or Both?

Kaidi Xu*, Shaokai Ye*, Sijia Liu, Jan-Henrik Lambrechts, Huan Zhang, Kaisheng Ma, Yanzhi Wang, Xue Lin

On the Design of Black-box Adversarial Examples by Leveraging Gradient-free Optimization and Operator Splitting Method

Pu Zhao, Sijia Liu, Pin-Yu Chen, Nghia Hoang, Kaidi Xu, Bhavya Kailkhura, Xue Lin

Topology Attack and Defense for Graph Neural Networks: An Optimization Perspective

Kaidi Xu, Hongge Chen, Sijia Liu, Pin-Yu Chen, Tsui-Wei Weng, Mingyi Hong, Xue Lin

Structured Adversarial Attack: Towards General Implementation and Better Interpretability

Kaidi Xu, Sijia Liu, Pu Zhao, Pin-Yu Chen, Huan Zhang, Deniz Erdogmus, Yanzhi Wang, Xue Lin

Interpreting Adversarial Examples by Activation Promotion and Suppression

Kaidi Xu, Sijia Liu, Gaoyuan Zhang, Mengshu Sun, Pu Zhao, Quanfu Fan, Chuang Gan, Xue Lin

REQ-YOLO: A Resource-Aware, Efficient Quantization Framework for Object Detection on FPGAs

Caiwen Ding, Shuo Wang, Ning Liu, Kaidi Xu, Yanzhi Wang, Yun Liang

ADMM Attack: An Enhanced Adversarial Attack for Deep Neural Networks with Undetectable Distortions

Pu Zhao, Kaidi Xu, Sijia Liu, Yanzhi Wang, Xue Lin

2018

Reinforced Adversarial Attacks on Deep Neural Networks Using ADMM

Pu Zhao, Kaidi Xu, Tianyun Zhang, Makan Fardad, Yanzhi Wang, Xue Lin

2017

Supervised Graph Hashing for Histopathology Image Retrieval and Classification

Xiaoshuang Shi, Fuyong Xing, Kaidi Xu, Yuanpu Xie, Hai Su, Lin Yang

Asymmetric Discrete Graph Hashing

Xiaoshuang Shi, Fuyong Xing, Kaidi Xu, Manish Sapkota, Lin Yang