The full list of publications can be found on Google Scholar.

2024

UnSeg: One Universal Unlearnable Example Generator is Enough against All Image Segmentation
Ye Sun, Hao Zhang, Tiehua Zhang, Xingjun Ma, Yu-Gang Jiang
Annual Conference on Neural Information Processing Systems (NeurIPS), Vancouver, Canada, 2024.

ModelLock: Locking Your Model With a Spell [Code]
Yifeng Gao, Yuhua Sun, Xingjun Ma, Zuxuan Wu, Yu-Gang Jiang
Brave New Ideas (BNI) Track, ACM International Conference on Multimedia (ACM MM), Melbourne, Australia, 2024.

White-box Multimodal Jailbreaks Against Large Vision-Language Models [Code]
Ruofan Wang, Xingjun Ma, Hanxu Zhou, Chuanjun Ji, Guangnan Ye, Yu-Gang Jiang
ACM International Conference on Multimedia (ACM MM), Melbourne, Australia, 2024.

AdvQDet: Detecting Query-Based Adversarial Attacks with Adversarial Contrastive Prompt Tuning [Code]
Xin Wang, Kai Chen, Xingjun Ma, Zhineng Chen, Jingjing Chen, Yu-Gang Jiang
ACM International Conference on Multimedia (ACM MM), Melbourne, Australia, 2024.

Fuse Your Latents: Video Editing with Multi-source Latent Diffusion Models [Code]
Tianyi Lu, Xing Zhang, Jiaxi Gu, Hang Xu, Renjing Pei, Songcen Xu, Xingjun Ma, Zuxuan Wu
ACM International Conference on Multimedia (ACM MM), Melbourne, Australia, 2024.

Adversarial Prompt Tuning for Vision-Language Models [Code]
Jiaming Zhang, Xingjun Ma, Xin Wang, Lingyu Qiu, Jiaqi Wang, Yu-Gang Jiang, Jitao Sang
European Conference on Computer Vision (ECCV), MiCo Milano, Italy, 2024.

Constrained Intrinsic Motivation for Reinforcement Learning
Xiang Zheng, Xingjun Ma, Chao Shen, Cong Wang
International Joint Conference on Artificial Intelligence (IJCAI), Jeju, Korea, 2024.

Toward Evaluating Robustness of Reinforcement Learning with Adversarial Policy
Xiang Zheng, Xingjun Ma, Shengjie Wang, Xinyu Wang, Chao Shen, Cong Wang
International Conference on Dependable Systems and Networks (DSN), Brisbane, Australia, 2024.

VeriFi: Towards Verifiable Federated Unlearning
Xiangshan Gao, Xingjun Ma, Jingyi Wang, Youcheng Sun, Bo Li, Shouling Ji, Peng Cheng, Jiming Chen
IEEE Transactions on Dependable and Secure Computing (TDSC), 2024.

Fake Alignment: Are LLMs Really Aligned Well?
Yixu Wang, Yan Teng, Kexin Huang, Chengqi Lyu, Songyang Zhang, Wenwei Zhang, Xingjun Ma, Yu-Gang Jiang, Yu Qiao, Yingchun Wang
Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), Mexico City, Mexico, 2024.

LDReg: Local Dimensionality Regularized Self-Supervised Learning [Code]
Hanxun Huang, Ricardo J. G. B. Campello, Sarah M. Erfani, Xingjun Ma, Michael E. Houle, James Bailey
International Conference on Learning Representations (ICLR), Vienna, Austria, 2024.

Unlearnable Examples For Time Series
Yujing Jiang, Xingjun Ma, Sarah Monazam Erfani and James Bailey
Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2024.

2023

Reconstructive Neuron Pruning for Backdoor Defense [Code]
Yige Li, Xixiang Lyu, Xingjun Ma, Nodens Koren, Lingjuan Lyu, Bo Li, Yu-Gang Jiang
International Conference on Machine Learning (ICML), Hawaii, USA, 2023.

Unlearnable Clusters: Towards Label-agnostic Unlearnable Examples [Code]
Jiaming Zhang, Xingjun Ma, Qi Yi, Jitao Sang, Yu-Gang Jiang, Yaowei Wang, Changsheng Xu
IEEE/CVF Computer Vision and Pattern Recognition Conference (CVPR), Vancouver, Canada, 2023.

Distilling Cognitive Backdoor Patterns within an Image [Code]
Hanxun Huang, Xingjun Ma, Sarah M. Erfani, James Bailey
International Conference on Learning Representations (ICLR), Kigali, Rwanda, 2023.

Transferable Unlearnable Examples [Code]
Jie Ren, Han Xu, Yuxuan Wan, Xingjun Ma, Lichao Sun, Jiliang Tang
International Conference on Learning Representations (ICLR), Kigali, Rwanda, 2023.

On the Importance of Spatial Relations for Few-shot Action Recognition [Code]
Yilun Zhang, Yuqian Fu, Xingjun Ma, Lizhe Qi, Jingjing Chen, Zuxuan Wu, Yu-Gang Jiang
ACM International Conference on Multimedia (ACM MM), Ottawa, Canada, 2023.

Backdoor Attacks on Time Series: A Generative Approach [Code]
Yujing Jiang, Xingjun Ma, Sarah M. Erfani, James Bailey
IEEE Conference on Secure and Trustworthy Machine Learning (SaTML), 2023.

Relationships between tail entropies and local intrinsic dimensionality and their use for estimation and feature representation
James Bailey, Michael E. Houle, Xingjun Ma
Information Systems (2023): 102245.

Imbalanced Gradients: A Subtle Cause of Overestimated Adversarial Robustness [Code]
Xingjun Ma^*, Linxi Jiang^*, Hanxun Huang, Zejia Weng, James Bailey, Yu-Gang Jiang
Machine Learning (2023): 1-26.

Query-efficient Black-box Adversarial Attacks on Automatic Speech Recognition [Code]
Chuxuan Tong, Xi Zheng, Jianhua Li, Xingjun Ma, Longxiang Gao, Yong Xiang
To appear in IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP).

2022

Local Intrinsic Dimensionality, Entropy and Statistical Divergences
James Bailey, Michael E. Houle, Xingjun Ma
Entropy 24(9), 1220, 2022.

Few-Shot Backdoor Attacks on Visual Object Tracking [Code]
Yiming Li, Haoxiang Zhong, Xingjun Ma, Yong Jiang, Shu-Tao Xia
International Conference on Learning Representations (ICLR), 2022.

CalFAT: Calibrated Federated Adversarial Training with Label Skewness
Chen Chen, Yuchen Liu, Xingjun Ma, Lingjuan Lyu
Advances in Neural Information Processing Systems (NeurIPS), 2022.

Copy, Right? A Testing Framework for Copyright Protection of Deep Learning Models [Code]
Jialuo Chen, Jingyi Wang, Tinglan Peng, Youcheng Sun, Peng Cheng, Shouling Ji, Xingjun Ma, Bo Li, Dawn Song
IEEE Symposium on Security and Privacy (Oakland), 2022.

Backdoor Attacks on Crowd Counting [Code]
Yuhua Sun, Tailai Zhang, Xingjun Ma, Pan Zhou, Jian Lou, Zichuan Xu, Xing Di, Yu Cheng, Lichao Sun
ACM International Conference on Multimedia (ACM MM), 2022.

Fine-mixing: Mitigating Backdoors in Fine-tuned Language Models
Zhiyuan Zhang, Lingjuan Lyu, Xingjun Ma, Chenguang Wang, Xu Sun
The 2022 Conference on Empirical Methods on Natural Language Processing (EMNLP), 2022.

Privacy and Robustness in Federated Learning: Attacks and Defenses
Lingjuan Lyu, Han Yu, Xingjun Ma, Chen Chen, Lichao Sun, Jun Zhao, Qiang Yang, Philip Yu
IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2022.

QuoTe: Quality-oriented Testing for Deep Learning Systems
Jialuo Chen, Jingyi Wang*, Xingjun Ma, Youcheng Sun, Jun Sun, Peixin Zhang and Peng Cheng
ACM Transactions on Software Engineering and Methodology (TOSEM) (accepted in 2022).

Machine learning guided alloy design of high-temperature NiTiHf shape memory alloys
Udesh M.H.U. Kankanamge, Johannes Reiner, Xingjun Ma, Santiago Corujeira Gallo, Wei Xu
Journal of Materials Science. (2022 Robert W. Cahn Best Paper Award)

2021

Exploring Architectural Ingredients of Adversarially Robust Deep Neural Networks [Code]
Hanxun Huang, Yisen Wang, Sarah M. Erfani, Quanquan Gu, James Bailey, Xingjun Ma
Advances in Neural Information Processing Systems (NeurIPS), 2021.

Alpha-IoU: A Family of Power Intersection over Union Losses for Bounding Box Regression [Code]
Jiabo He, Sarah M. Erfani, Xingjun Ma, James Bailey, Ying Chi, Xian-Sheng Hua
Advances in Neural Information Processing Systems (NeurIPS), 2021.

Anti-Backdoor Learning: Training Clean Models on Poisoned Data [Code]
Yige Li, Xixiang Lyu, Nodens Koren, Lingjuan Lyu, Bo Li, Xingjun Ma
Advances in Neural Information Processing Systems (NeurIPS), 2021.

Gradient Driven Rewards to Guarantee Fairness in Collaborative Machine Learning [Code]
Xinyi Xu, Lingjuan Lyu, Xingjun Ma, Chenglin Miao, Chuan-Sheng Foo, Kian H. Low
Advances in Neural Information Processing Systems (NeurIPS), 2021.

Unlearnable Examples: Making Personal Data Unexploitable [Code] [Webpage]
Hanxun Huang, Xingjun Ma, Sarah M. Erfani, James Bailey, Yisen Wang
International Conference on Learning Representations (ICLR), 2021. (Spotlight, top 4%)
Press: MIT Technology Review, PURSUIT, Gadgets 360

Neural Attention Distillation: Erasing Backdoor Triggers from Deep Neural Networks [Code]
Yige Li, Xixiang Lyu, Nodens Koren, Lingjuan Lyu, Bo Li, Xingjun Ma
International Conference on Learning Representations (ICLR), 2021.

Improving Adversarial Robustness via Channel-wise Activation Suppressing [Code]
Yang Bai, Yuyuan Zeng, Yong Jiang, Shu-Tao Xia, Xingjun Ma, Yisen Wang
International Conference on Learning Representations (ICLR), 2021. (Spotlight, top 4%)

Revisiting Adversarial Robustness Distillation: Robust Soft Labels Make Student Better [Code]
Bojia Zi^*, Shihao Zhao^*, Xingjun Ma, Yu-Gang Jiang
International Conference on Computer Vision (ICCV), 2021.

Noise Doesn’t Lie: Towards Universal Detection of Deep Inpainting
Ang Li, Qiuhong Ke, Xingjun Ma, Haiqin Weng, Zhiyuan Zong, Feng Xue, Rui Zhang
International Joint Conference on Artificial Intelligence (IJCAI), 2021.

Relationships between Local Intrinsic Dimensionality and Tail Entropy [Video]
James Bailey, Michael Houle, Xingjun Ma
International Conference on Similarity Search and Applications (SISAP), Dortmund, Germany, 2021. (Best Paper Award)

RobOT: Robustness-Oriented Testing for Deep Learning Systems [Tookit]
Jingyi Wang, Jialuo Chen, Youcheng Sun, Xingjun Ma, Dongxia Wang, Jun Sun, Peng Cheng
International Conference on Software Engineering (ICSE), 2021.

Sub-trajectory Similarity Join with Obfuscation
Yanchuan Chang, Jianzhong Qi, Egemen Tanin, Xingjun Ma, Hanan Samet
International Conference on Scientific and Statistical Database Management (SSDBM), 2021. (Best Paper Runner-up Award)

SpineOne: A One-Stage Detection Framework for Degenerative Discs and Vertebrae
Jiabo He, Wei Liu, Yu Wang, Xingjun Ma, Xian-Sheng Hua
IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2021.

Dual Head Adversarial Training [Code]
Yujing Jiang, Xingjun Ma, Sarah M. Erfani, James Bailey
International Joint Conference on Neural Networks (IJCNN), 2021.

Neural Architecture Search via Combinatorial Multi-Armed Bandit
Hanxun Huang, Xingjun Ma, Sarah M. Erfani, James Bailey
International Joint Conference on Neural Networks (IJCNN), 2021.

Federated Learning with Extreme Label Skew: A Data Extension Approach
Saheed Tijani, Xingjun Ma, Frank Jiang, Robin Doss
International Joint Conference on Neural Networks (IJCNN), 2021.

Microwave Link Failures Prediction via LSTM-based Feature Fusion Network
Zichan Ruan, Shuiqiao Yang, Lei Pan, Xingjun Ma, Wei Luo, Marthie Grobler
International Joint Conference on Neural Networks (IJCNN), 2021.

Anomaly Detection for Scenario-based Insider Activities using CGAN Augmented Data
R G Gayathri, Atul Sajjanhar, Yong Xiang, Xingjun Ma
International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom), 2021.

ECG-Adv-GAN: Detecting ECG Adversarial Examples with Conditional Generative Adversarial Networks
Khondker Fariha Hossain, Sharif Amit Kamran, Alireza Tavakkoli, Lei Pan, Xingjun Ma, Sutharshan Rajasegarar, Chandan Karmaker
International Conference on Machine Learning and Applications (ICMLA), 2021.

Exploring the Vulnerability of Natural Language Processing Models via Universal Adversarial Texts
Xinzhe Li, Ming Liu, Xingjun Ma, Longxiang Gao
Australasian Language Technology Association Workshop (ALTA), 2021.

Surgical approach to the facial recess influences the acceptable trajectory of cochlear implantation electrodes
Bridget Copson, Sudanthi Wijewickrema, Xingjun Ma, Yun Zhou, Jean-Marc Gerard, Stephen O’Leary
European Archives of Oto-Rhino-Laryngology, 1-11, 2021.

2020

Normalized Loss Functions for Deep Learning with Noisy Labels [Code]
Xingjun Ma^*, Hanxun Huang^*, Yisen Wang, Simone Romano, Sarah M. Erfani, James Bailey
International Conference on Machine Learning (ICML), 2020.

Improving Adversarial Robustness Requires Revisiting Misclassified Examples [Code]
Yisen Wang, Difan Zou, Jinfeng Yi, James Bailey, Xingjun Ma, Quanquan Gu
International Conference on Learning Representations (ICLR), 2020.

Skip Connections Matter: on the Transferability of Adversarial Examples Generated with ResNets [Code]
Dongxian Wu, Yisen Wang, Shu-Tao Xia, James Bailey, Xingjun Ma
International Conference on Learning Representations (ICLR), 2020. (Spotlight, top 4%)

Understanding Adversarial Attacks on Deep Learning Based Medical Image Analysis Systems [Code]
Xingjun Ma^*, Yuhao Niu^*, Lin Gu, Yisen Wang, Yitian Zhao, James Bailey, Feng Lu
Pattern Recognition (PR), 110, 2021, 107332. (accepted in 2020)
Press: Computer Vision News

Clean-Label Backdoor Attacks on Video Recognition Models [Code]
Shihao Zhao, Xingjun Ma, Xiang Zheng, James Bailey, Jingjing Chen, Yu-Gang Jiang
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020.

Adversarial Camouflage: Hiding Physical-World Attacks with Natural Styles [Code]
Ranjie Duan, Xingjun Ma, Yisen Wang, James Bailey, Kai Qin, Yun Yang
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020.

WildDeepfake: A Challenging Real-World Dataset for Deepfake Detection [Dataset/Code]
Bojia Zi, Jingjing Chen, Minghao Chang, Xingjun Ma, Yu-Gang Jiang
ACM International Conference on Multimedia (ACM MM), 2020.

Reflection Backdoor: A Natural Backdoor Attack on Deep Neural Networks [Code]
Yunfei Liu, Xingjun Ma, James Bailey, Feng Lu
European Conference on Computer Vision (ECCV), 2020.

Short-Term and Long-Term Context Aggregation Network for Video Inpainting
Ang Li, Shanshan Zhao, Xingjun Ma, Mingming Gong, Jianzhong Qi, Rui Zhang, Dacheng Tao, Ramamohanarao Kotagiri
European Conference on Computer Vision (ECCV), 2020. (Spotlight, top 5%)

Transfer of Automated Performance Feedback Models to Different Specimens in Virtual Reality Temporal Bone Surgery
Jesslyn Lamtara, Nathan Hanegbi, Benjamin Talks, Sudanthi Wijewickrema, Xingjun Ma, Patorn Piromchai, James Bailey, Stephen O’Leary
International Conference on Artificial Intelligence in Education (AIED), 2020.

Towards Fair and Privacy-Preserving Federated Deep Models [Code] [Medium] [Youtube]
Lingjuan Lyu, Jiangshan Yu, Karthik Nandakumar, Yitong Li, Xingjun Ma, Jiong Jin, Han Yu, Kee Siong Ng
IEEE Transactions on Parallel and Distributed Systems (TPDS). (accepted in 2020)

How to Democratise and Protect AI: Fair and Differentially Private Decentralised Deep Learning
Lingjuan Lyu, Yitong Li, Karthik, Nandakumar, Jiangshan Yu, Xingjun Ma
IEEE Transactions on Dependable and Secure Computing (TDSC). (accepted in 2020)

2019

On the Convergence and Robustness of Adversarial Training [Code]
Yisen Wang^*, Xingjun Ma^*, James Bailey, Jinfeng Yi, Bowen Zhou, Quanquan Gu
International Conference on Machine Learning (ICML), Long Beach, USA, 2019. (Long talk, top 3%)

Symmetric Cross Entropy for Robust Learning with Noisy Labels [Code]
Yisen Wang^*, Xingjun Ma^*, Zaiyi Chen, Yuan Luo, Jinfeng Yi, James Bailey
International Conference on Computer Vision (ICCV), Seoul, Korea, 2019.

Black-box Adversarial Attacks on Video Recognition Models [Code]
Linxi Jiang^*, Xingjun Ma^*, Shaoxiang Chen, James Bailey, Yu-Gang Jiang
ACM International Conference on Multimedia (ACM MM), Nice, France, 2019.

Generative Image Inpainting with Submanifold Alignment
Ang Li, Jianzhong Qi, Rui Zhang, Xingjun Ma, Ramamohanarao Kotagiri
International Joint Conference on Artificial Intelligence (IJCAI), Macao, China, 2019.

Exploiting Patterns to Explain Individual Predictions
Yunzhe Jia, James Bailey, Ramamohanarao Kotagiri, Christopher Leckie, Xingjun Ma
Knowledge and Information Systems (KAIS). (accepted in 2019)

Quality Eva

2018

Characterizing Adversarial Subspaces Using Local Intrinsic Dimensionality [Code]
Xingjun Ma, Bo Li, Yisen Wang, Sarah M. Erfani, Sudanthi Wijewickrema, Grant Schoenebeck, Dawn Song, Michael E. Houle, James Bailey
International Conference on Learning Representations (ICLR), Vancouver, BC, Canada, 2018, (Oral, top 2%)

Dimensionality-Driven Learning with Noisy Labels [Code]
Xingjun Ma^*, Yisen Wang^*, Michael E. Houle, Shuo Zhou, Sarah M. Erfani, Shu-Tao Xia, Sudanthi Wijewickrema, James Bailey
International Conference on Machine Learning (ICML), Stockholm, Sweden, 2018. (Long talk, top 4%)

Iterative Learning with Open-set Noisy Labels
Yisen Wang, Weiyang Liu, Xingjun Ma, James Bailey, Hongyuan Zha, Le Song, Shu-Tao Xia
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Salt Lake City, Utah, USA, 2018. (Spotlight, top 6%)

Providing Automated Real-Time Technical Feedback for Virtual Reality Based Surgical Training: Is the Simpler the Better?
Sudanthi Wijewickrema, Xingjun Ma, Patorn Piromchai, Robert Briggs, James Bailey, Gregor Kennedy, Stephen O’Leary
International Conference on Artificial Intelligence in Education (AIED), London, UK, 2018

Development and Validation of a Virtual Reality Tutor to Teach Clinically Oriented Surgical Anatomy of the Ear
Sudanthi Wijewickrema, Bridget Copson, Xingjun Ma, Robert Briggs, James Bailey, Gregor Kennedy, Stephen O’Leary
IEEE International Symposium on Computer-Based Medical Systems (CBMS), 2018

2017

Adversarial Generation of Real-time Feedback with Neural Networks for Simulation-based Training
Xingjun Ma, Sudanthi Wijewickrema, Shuo Zhou, Yun Zhou, Zakaria Mhammedi, Stephen O’Leary, James Bailey.
International Joint Conference on Artificial Intelligence (IJCAI), Melbourne, Australia, 2017. (Oral)

Unbiased Multivariate Correlation Analysis
Yisen Wang, Simone Romano, Nguyen Xuan Vinh, James Bailey, Xingjun Ma, Shu-Tao Xia
AAAI Conference on Artificial Intelligence (AAAI), San Francisco, USA, 2017. (Oral)

Providing Effective Real-time Feedback in Simulation-based Surgical Training
Xingjun Ma, Sudanthi Wijewickrema, Yun Zhou, Shuo Zhou, Stephen O’Leary, James Bailey
International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Quebec City, Canada, 2017.

Simulation for Training Cochlear Implant Electrode Insertion
Xingjun Ma, Sudanthi Wijewickremay, Yun Zhou, Bridget Copson, James Bailey, Gregor Kennedy, Stephen O’Leary
IEEE International Symposium on Computer-Based Medical Systems (CBMS), Thessaloniki, Greece, 2017

Design and Evaluation of a Virtual Reality Simulation Module for Training Advanced Temporal Bone Surgery
Sudanthi Wijewickremay, Bridget Copson, Yun Zhou, Xingjun Ma, Robert Briggs, James Bailey, Gregor Kennedy, Stephen O’Leary
IEEE International Symposium on Computer-Based Medical Systems (CBMS), Thessaloniki, Greece, 2017

Feedback Techniques in Computer-Based Simulation Training: A Survey
Sudanthi Wijewickrema, Xingjun Ma, James Bailey, Gregor Kennedy and Stephen O’Leary
arXiv preprint. –>

2016

Finding Influentials in Twitter: A Temporal Influence Ranking Model [Paper]
Xingjun Ma, Chunping Li, James Bailey, Sudanthi Wijewickrema
The Australasian Data Mining Conference (AusDM), Canberra, Australia, 2016