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Hanxun Huang
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2020 – today
- 2026
- [j5]Zaher Joukhadar
, Hanxun Huang, Sarah Monazam Erfani, Ricardo J. G. B. Campello, Michael E. Houle, James Bailey:
A Bayesian framework for robust local intrinsic dimensionality estimation. Inf. Syst. 138: 102668 (2026) - [j4]Yige Li
, Jiabo He
, Hanxun Huang
, Jun Sun
, Xingjun Ma
, Yu-Gang Jiang
:
Shortcuts Everywhere and Nowhere: Exploring Multi-Trigger Backdoor Attacks. IEEE Trans. Dependable Secur. Comput. 23(1): 343-355 (2026) - [j3]Jiacheng Zhang, Jinhao Li, Hanxun Huang, Sarah Monazam Erfani, Benjamin I. P. Rubinstein, Feng Liu:
Semantic-aware Adversarial Fine-tuning for CLIP. Trans. Mach. Learn. Res. 2026 (2026) - [i24]Xiang Zheng, Yutao Wu, Hanxun Huang, Yige Li, Xingjun Ma, Bo Li, Yu-Gang Jiang, Cong Wang:
Just Ask: Curious Code Agents Reveal System Prompts in Frontier LLMs. CoRR abs/2601.21233 (2026) - [i23]Kaiyuan Cui, Yige Li, Yutao Wu, Xingjun Ma, Sarah M. Erfani, Christopher Leckie, Hanxun Huang:
Toward Universal and Transferable Jailbreak Attacks on Vision-Language Models. CoRR abs/2602.01025 (2026) - [i22]Jiacheng Zhang, Jinhao Li, Hanxun Huang, Sarah M. Erfani, Benjamin I. P. Rubinstein, Feng Liu:
Semantic-aware Adversarial Fine-tuning for CLIP. CoRR abs/2602.12461 (2026) - [i21]Yige Li, Wei Zhao, Zhe Li, Nay Myat Min, Hanxun Huang, Yunhan Zhao, Xingjun Ma, Yu-Gang Jiang, Jun Sun:
Backdoor4Good: Benchmarking Beneficial Uses of Backdoors in LLMs. CoRR abs/2603.07452 (2026) - [i20]Yutao Wu, Xiao Liu, Yifeng Gao, Xiang Zheng, Hanxun Huang, Yige Li, Cong Wang, Bo Li, Xingjun Ma, Yu-Gang Jiang:
Internal Safety Collapse in Frontier Large Language Models. CoRR abs/2603.23509 (2026) - 2025
- [j2]Xingjun Ma, Yifeng Gao, Yixu Wang, Ruofan Wang, Xin Wang
, Ye Sun, Yifan Ding, Hengyuan Xu, Yunhao Chen, Yunhao Zhao, Hanxun Huang, Yige Li, Yutao Wu
, Jiaming Zhang, Xiang Zheng, Yang Bai, Yiming Li, Zuxuan Wu, Xipeng Qiu, Jingfeng Zhang, Xudong Han, Haonan Li, Jun Sun, Cong Wang, Jindong Gu, Baoyuan Wu, Siheng Chen, Tianwei Zhang, Yang Liu, Mingming Gong, Tongliang Liu, Shirui Pan, Cihang Xie, Tianyu Pang, Yinpeng Dong, Ruoxi Jia, Yang Zhang, Shiqing Ma, Xiangyu Zhang, Neil Gong, Chaowei Xiao, Sarah M. Erfani, Tim Baldwin, Bo Li, Masashi Sugiyama, Dacheng Tao, James Bailey, Yu-Gang Jiang:
Safety at Scale: A Comprehensive Survey of Large Model and Agent Safety. Found. Trends Priv. Secur. 8(3-4): 254-469 (2025) - [c11]Yong Xie, Weijie Zheng, Hanxun Huang, Guangnan Ye, Xingjun Ma:
Towards Million-Scale Adversarial Robustness Evaluation With Stronger Individual Attacks. CVPR 2025: 30702-30711 - [c10]Hanxun Huang, Sarah Monazam Erfani, Yige Li, Xingjun Ma, James Bailey:
Detecting Backdoor Samples in Contrastive Language Image Pretraining. ICLR 2025 - [c9]Hanxun Huang, Sarah Monazam Erfani, Yige Li, Xingjun Ma, James Bailey:
X-Transfer Attacks: Towards Super Transferable Adversarial Attacks on CLIP. ICML 2025 - [c8]Xingjun Ma
, Hanxun Huang
, Tianwei Song
, Ye Sun
, Yifeng Gao
, Yu-Gang Jiang
:
T2UE: Generating Unlearnable Examples from Text Descriptions. ACM Multimedia 2025: 12257-12265 - [i19]Hanxun Huang, Sarah M. Erfani, Yige Li, Xingjun Ma, James Bailey:
Detecting Backdoor Samples in Contrastive Language Image Pretraining. CoRR abs/2502.01385 (2025) - [i18]Xingjun Ma, Yifeng Gao, Yixu Wang, Ruofan Wang, Xin Wang, Ye Sun, Yifan Ding, Hengyuan Xu, Yunhao Chen, Yunhan Zhao, Hanxun Huang, Yige Li, Jiaming Zhang, Xiang Zheng, Yang Bai, Zuxuan Wu, Xipeng Qiu, Jingfeng Zhang, Yiming Li, Jun Sun, Cong Wang, Jindong Gu, Baoyuan Wu, Siheng Chen, Tianwei Zhang, Yang Liu, Mingming Gong, Tongliang Liu, Shirui Pan, Cihang Xie, Tianyu Pang, Yinpeng Dong, Ruoxi Jia, Yang Zhang, Shiqing Ma, Xiangyu Zhang, Neil Gong, Chaowei Xiao, Sarah M. Erfani, Bo Li, Masashi Sugiyama, Dacheng Tao
, James Bailey, Yu-Gang Jiang:
Safety at Scale: A Comprehensive Survey of Large Model Safety. CoRR abs/2502.05206 (2025) - [i17]Canaan Yung, Hanxun Huang, Sarah Monazam Erfani, Christopher Leckie:
CURVALID: Geometrically-guided Adversarial Prompt Detection. CoRR abs/2503.03502 (2025) - [i16]Hanxun Huang, Sarah M. Erfani, Yige Li, Xingjun Ma, James Bailey:
X-Transfer Attacks: Towards Super Transferable Adversarial Attacks on CLIP. CoRR abs/2505.05528 (2025) - [i15]Xingjun Ma, Hanxun Huang, Tianwei Song, Ye Sun, Yifeng Gao, Yu-Gang Jiang:
T2UE: Generating Unlearnable Examples from Text Descriptions. CoRR abs/2508.03091 (2025) - [i14]Qizhou Wang, Hanxun Huang, Guansong Pang, Sarah M. Erfani, Christopher Leckie:
AUDETER: A Large-scale Dataset for Deepfake Audio Detection in Open Worlds. CoRR abs/2509.04345 (2025) - [i13]Yige Li, Zhe Li, Wei Zhao, Nay Myat Min, Hanxun Huang, Xingjun Ma, Jun Sun:
AutoBackdoor: Automating Backdoor Attacks via LLM Agents. CoRR abs/2511.16709 (2025) - [i12]Juncheng Li, Yige Li, Hanxun Huang, Yunhao Chen, Xin Wang, Yixu Wang, Xingjun Ma, Yu-Gang Jiang:
BackdoorVLM: A Benchmark for Backdoor Attacks on Vision-Language Models. CoRR abs/2511.18921 (2025) - 2024
- [b1]Hanxun Huang:
Robust and Trustworthy Machine Learning. University of Melbourne, Parkville, Victoria, Australia, 2024 - [j1]Xingjun Ma, Linxi Jiang, Hanxun Huang
, Zejia Weng, James Bailey, Yu-Gang Jiang:
Imbalanced gradients: a subtle cause of overestimated adversarial robustness. Mach. Learn. 113(5): 2301-2326 (2024) - [c7]Hanxun Huang, Ricardo J. G. B. Campello, Sarah Monazam Erfani, Xingjun Ma, Michael E. Houle, James Bailey:
LDReg: Local Dimensionality Regularized Self-Supervised Learning. ICLR 2024 - [c6]Zaher Joukhadar
, Hanxun Huang
, Sarah Monazam Erfani
, Ricardo J. G. B. Campello
, Michael E. Houle
, James Bailey
:
Bayesian Estimation Approaches for Local Intrinsic Dimensionality. SISAP 2024: 111-125 - [i11]Hanxun Huang, Ricardo J. G. B. Campello, Sarah Monazam Erfani, Xingjun Ma, Michael E. Houle, James Bailey:
LDReg: Local Dimensionality Regularized Self-Supervised Learning. CoRR abs/2401.10474 (2024) - [i10]Yige Li, Xingjun Ma, Jiabo He, Hanxun Huang, Yu-Gang Jiang:
Multi-Trigger Backdoor Attacks: More Triggers, More Threats. CoRR abs/2401.15295 (2024) - [i9]Weijie Zheng, Xingjun Ma, Hanxun Huang, Zuxuan Wu, Yu-Gang Jiang:
Downstream Transfer Attack: Adversarial Attacks on Downstream Models with Pre-trained Vision Transformers. CoRR abs/2408.01705 (2024) - [i8]Yige Li, Hanxun Huang, Yunhan Zhao, Xingjun Ma, Jun Sun:
BackdoorLLM: A Comprehensive Benchmark for Backdoor Attacks on Large Language Models. CoRR abs/2408.12798 (2024) - [i7]Yige Li, Hanxun Huang, Jiaming Zhang, Xingjun Ma, Yu-Gang Jiang:
Expose Before You Defend: Unifying and Enhancing Backdoor Defenses via Exposed Models. CoRR abs/2410.19427 (2024) - [i6]Yong Xie, Weijie Zheng, Hanxun Huang, Guangnan Ye, Xingjun Ma:
Towards Million-Scale Adversarial Robustness Evaluation With Stronger Individual Attacks. CoRR abs/2411.15210 (2024) - 2023
- [c5]Hanxun Huang, Xingjun Ma, Sarah Monazam Erfani, James Bailey:
Distilling Cognitive Backdoor Patterns within an Image. ICLR 2023 - [i5]Hanxun Huang
, Xingjun Ma, Sarah M. Erfani, James Bailey:
Distilling Cognitive Backdoor Patterns within an Image. CoRR abs/2301.10908 (2023) - 2021
- [c4]Hanxun Huang, Xingjun Ma, Sarah Monazam Erfani, James Bailey, Yisen Wang:
Unlearnable Examples: Making Personal Data Unexploitable. ICLR 2021 - [c3]Hanxun Huang
, Xingjun Ma, Sarah M. Erfani, James Bailey:
Neural Architecture Search via Combinatorial Multi-Armed Bandit. IJCNN 2021: 1-8 - [c2]Hanxun Huang, Yisen Wang, Sarah M. Erfani, Quanquan Gu, James Bailey, Xingjun Ma:
Exploring Architectural Ingredients of Adversarially Robust Deep Neural Networks. NeurIPS 2021: 5545-5559 - [i4]Hanxun Huang, Xingjun Ma, Sarah M. Erfani, James Bailey:
Neural Architecture Search via Combinatorial Multi-Armed Bandit. CoRR abs/2101.00336 (2021) - [i3]Hanxun Huang, Xingjun Ma, Sarah Monazam Erfani, James Bailey, Yisen Wang:
Unlearnable Examples: Making Personal Data Unexploitable. CoRR abs/2101.04898 (2021) - [i2]Hanxun Huang, Yisen Wang, Sarah Monazam Erfani, Quanquan Gu, James Bailey, Xingjun Ma:
Exploring Architectural Ingredients of Adversarially Robust Deep Neural Networks. CoRR abs/2110.03825 (2021) - 2020
- [c1]Xingjun Ma, Hanxun Huang, Yisen Wang, Simone Romano, Sarah M. Erfani, James Bailey:
Normalized Loss Functions for Deep Learning with Noisy Labels. ICML 2020: 6543-6553 - [i1]Xingjun Ma, Hanxun Huang, Yisen Wang, Simone Romano, Sarah M. Erfani, James Bailey:
Normalized Loss Functions for Deep Learning with Noisy Labels. CoRR abs/2006.13554 (2020)
Coauthor Index
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last updated on 2026-05-07 01:50 CEST by the dblp team
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