Normalized Loss Functions for Deep Learning with Noisy Labels. - Xingjun Ma; Hanxun Huang; Yisen Wang 001; Simone Romano 003; Sarah M. Erfani; James Bailey 001 (ICML, 2020)

Unlearnable Examples: Making Personal Data Unexploitable. - Hanxun Huang; Xingjun Ma; Sarah Monazam Erfani; James Bailey 001; Yisen Wang 001 (ICLR, 2021)

Neural Architecture Search via Combinatorial Multi-Armed Bandit. - Hanxun Huang; Xingjun Ma; Sarah M. Erfani; James Bailey 001 (IJCNN, 2021)

Exploring Architectural Ingredients of Adversarially Robust Deep Neural Networks. - Hanxun Huang; Yisen Wang 001; Sarah M. Erfani; Quanquan Gu; James Bailey 001; Xingjun Ma (NeurIPS, 2021)

Distilling Cognitive Backdoor Patterns within an Image. - Hanxun Huang; Xingjun Ma; Sarah Monazam Erfani; James Bailey 001 (ICLR, 2023)

LDReg: Local Dimensionality Regularized Self-Supervised Learning. - Hanxun Huang; Ricardo J. G. B. Campello; Sarah Monazam Erfani; Xingjun Ma; Michael E. Houle; James Bailey 001 (ICLR, 2024)

Bayesian Estimation Approaches for Local Intrinsic Dimensionality. - Zaher Joukhadar; Hanxun Huang; Sarah Monazam Erfani; Ricardo J. G. B. Campello; Michael E. Houle; James Bailey 001 (SISAP, 2024)

Multi-Trigger Backdoor Attacks: More Triggers, More Threats. - Yige Li; Xingjun Ma; Jiabo He; Hanxun Huang; Yu-Gang Jiang 001 (CoRR, 2024)

Downstream Transfer Attack: Adversarial Attacks on Downstream Models with Pre-trained Vision Transformers. - Weijie Zheng; Xingjun Ma; Hanxun Huang; Zuxuan Wu; Yu-Gang Jiang 001 (CoRR, 2024)

BackdoorLLM: A Comprehensive Benchmark for Backdoor Attacks on Large Language Models. - Yige Li; Hanxun Huang; Yunhan Zhao; Xingjun Ma; Jun Sun 001 (CoRR, 2024)

Expose Before You Defend: Unifying and Enhancing Backdoor Defenses via Exposed Models. - Yige Li; Hanxun Huang; Jiaming Zhang 006; Xingjun Ma; Yu-Gang Jiang 001 (CoRR, 2024)

Robust and Trustworthy Machine Learning. - Hanxun Huang (2024)

Imbalanced gradients: a subtle cause of overestimated adversarial robustness. - Xingjun Ma; Linxi Jiang; Hanxun Huang; Zejia Weng; James Bailey 001; Yu-Gang Jiang 001 (Mach. Learn., 2024)

Towards Million-Scale Adversarial Robustness Evaluation With Stronger Individual Attacks. - Yong Xie; Weijie Zheng; Hanxun Huang; Guangnan Ye; Xingjun Ma (CVPR, 2025)

Detecting Backdoor Samples in Contrastive Language Image Pretraining. - Hanxun Huang; Sarah Monazam Erfani; Yige Li; Xingjun Ma; James Bailey 001 (ICLR, 2025)

Safety at Scale: A Comprehensive Survey of Large Model Safety. - Xingjun Ma; Yifeng Gao; Yixu Wang; Ruofan Wang; Xin Wang; Ye Sun; Yifan Ding; Hengyuan Xu; Yunhao Chen; Yunhan Zhao; Hanxun Huang; Yige Li; et al. (CoRR, 2025)

CURVALID: Geometrically-guided Adversarial Prompt Detection. - Canaan Yung; Hanxun Huang; Sarah Monazam Erfani; Christopher Leckie (CoRR, 2025)

X-Transfer Attacks: Towards Super Transferable Adversarial Attacks on CLIP. - Hanxun Huang; Sarah M. Erfani; Yige Li; Xingjun Ma; James Bailey 001 (CoRR, 2025)

T2UE: Generating Unlearnable Examples from Text Descriptions. - Xingjun Ma; Hanxun Huang; Tianwei Song; Ye Sun; Yifeng Gao; Yu-Gang Jiang 001 (CoRR, 2025)