SELECTED PUBLICATIONS

Full publication list can be found on Google Scholar. * indicates equal contribution and ♠ indicates corresponding author.

Books

• Chapter: Deepfake in Metaverse
  Wenbo Zhou, Aishan Liu, Cihang Xie, Nenghai Yu
  Handbook of Metaverse, Springer, 2023. (To Appear)
  [Books]


• Chapter 8: Explainable Artificial Intelligence in Computer Vision
  Aishan Liu, Xianglong Liu, Dacheng Tao
  Introduction to Explainable Artificial Intelligence (可解释人工智能导论), 电子工业出版社, 2022.
  [Books]



2024

• BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks
  Yisong Xiao, Aishan Liu^♠, Tianyuan Zhang, Xinwei Zhang, Siyuan Liang, Tianlin Li, Xianglong Liu, Yang Liu, Dacheng Tao
  IEEE/ACM International Conference on Software Engineering (ICSE), 2025.
  [Paper] [Code]


• LLMCBench: Benchmarking Large Language Model Compression for Efficient Deployment
  Ge Yang, Changyi He, Jinyang Guo, Jianyu Wu, Yifu Ding, Aishan Liu, Haotong Qin, Pengliang Ji, Xianglong Liu
  The Thirty-eight Conference on Neural Information Processing Systems Datasets and Benchmarks Track (NeurIPS D&B), 2024.
  [Paper] [Code]


• 面向大语言模型的越狱攻击与防御综述
  梁思源, 何英哲, 李京知, 刘艾杉, 代朋纹, 操晓春
  信息安全学报 (Journal of Cyber Security), 2024.
  [Paper] [Code]


• LanEvil: Benchmarking the Robustness of Lane Detection to Environmental Illusions
  Tianyuan Zhang, Lu Wang, Hainan Li, Yisong Xiao, Siyuan Liang, Aishan Liu^♠, Xianglong Liu, Dacheng Tao
  ACM Multimedia (ACM MM), 2024.
  [Paper] [Code]


• Towards Robust Physical-world Backdoor Attacks on Lane Detection
  Xinwei Zhang, Aishan Liu^♠, Tianyuan Zhang, Siyuan Liang, Xianglong Liu
  ACM Multimedia (ACM MM), 2024.
  [Paper] [Code]


• PTSBench: A Comprehensive Post-Training Sparsity Benchmark Towards Algorithms and Models
  Zining Wang, Jinyang Guo, Ruihao Gong, Yang Yong, Aishan Liu, Yushi Huang, Jiaheng Liu, Xianglong Liu
  ACM Multimedia (ACM MM), 2024.
  [Paper] [Code]


• Generate Transferable Adversarial Physical Camouflages via Triplet Attention Suppression
  Jiakai Wang, Xianglong Liu, Zixin Yin, Yuxuan Wang, Jun Guo, Haotong Qin, Qingtao Wu, Aishan Liu
  International Journal of Computer Vision (IJCV), 2024.
  [Paper] [Code]


• GenderCARE: A Comprehensive Framework for Assessing and Reducing Gender Bias in Large Language Models
  Kunsheng Tang, Wenbo Zhou, Jie Zhang, Aishan Liu, Gelei Deng, Shuai Li, Peigui Qi, Weiming Zhang, Tianwei Zhang, NengHai Yu
  ACM Conference on Computer and Communications Security (ACM CCS), 2024.
  [Paper] [Code]


• Hierarchical Perceptual Noise Injection for Social Media Fingerprint Privacy Protection
  Simin Li, Huangxinxin Xu, Jiakai Wang, Ruixiao Xu, Aishan Liu^♠, Fazhi He^♠, Xianglong Liu, and Dacheng Tao
  IEEE Transactions on Image Processing (IEEE TIP), 2024.
  [Paper] [Code]


• BadCLIP: Dual-Embedding Guided Backdoor Attack on Multimodal Contrastive Learning
  Siyuan Liang, Mingli Zhu, Aishan Liu^♠, Baoyuan Wu, Xiaochun Cao, Ee-Chien Chang^♠
  IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2024.
  [Paper] [Code]


• Poisoned Forgery Face: Towards Backdoor Attacks on Face Forgery Detection
  Jiawei Liang, Siyuan Liang, Aishan Liu, Xiaojun Jia, Junhao Kuang, Xiaochun Cao
  International Conference on Learning Representations (ICLR), 2024.
  [Paper] [Code] (Spotlight)


• Byzantine Robust Cooperative Multi-Agent Reinforcement Learning as a Bayesian Game
  Simin Li, Jun Guo, Jingqiao Xiu, Ruixiao Xu, Xin Yu, Jiakai Wang, Aishan Liu, Yaodong Yang, Xianglong Liu
  International Conference on Learning Representations (ICLR), 2024.
  [Paper] [Code]


• Improving Deepfake Detection Generalization by Invariant Risk Minimization
  Zixin Yin, Jiakai Wang, Yisong Xiao, Hanqing Zhao, Tianlin Li, Wenbo Zhou, Aishan Liu^♠, Xianglong Liu^♠
  IEEE Transactions on Multimedia (IEEE TMM), 2024.
  [Paper] [Code]


• Transferable Multimodal Attack on Vision-Language Pre-training Models
  Haodi Wang, Jiakai Wang, Kai Dong, Zhilei Zhu, Haotong Qin, Xiaolin Fang, Aishan Liu, Xianglong Liu
  IEEE Symposium on Security and Privacy (IEEE S&P), 2024.
  [Paper] [Code]



2023

• RUNNER: Responsible UNfair NEuron Repair for Enhancing Deep Neural Network Fairness
  Tianlin Li, Yue Cao, Jian Zhang, Shiqian Zhao, Yihao Huang, Aishan Liu, Qing Guo, Yang Liu
  International Conference on Software Engineering (ICSE), 2024.
  [Paper] [Code]


• Towards Defending Multiple Lp-norm Bounded Adversarial Perturbations via Gated Batch Normalization
  Aishan Liu, Shiyu Tang, Xinyun Chen, Lei Huang, Haotong Qin, Xianglong Liu, Dacheng Tao
  International Journal of Computer Vision (IJCV), 2023.
  [Paper] [Code]


• RobustMQ: Benchmarking Robustness of Quantized Models
  Yisong Xiao, Aishan Liu^♠, Tianyuan Zhang, Haotong Qin, Jinyang Guo, Xianglong Liu^♠
  Visual Intelligence (VIN), 2023.
  [Paper] [Code]


• Isolation and Induction: Training Robust Deep Neural Networks against Model Stealing Attacks
  Jun Guo, Aishan Liu^♠, Xingyu Zheng, Siyuan Liang, Yisong Xiao, Yichao Wu, Xianglong Liu
  ACM Multimedia (ACM MM), 2023.
  [Paper] [Code]


• Face Encryption via Frequency-Restricted Identity-Agnostic Attacks
  Xin Dong, Rui Wang, Siyuan Liang, Aishan Liu, Lihua Jing
  ACM Multimedia (ACM MM), 2023.
  [Paper] [Code] (Oral)


• Exploring Inconsistent Knowledge Distillation for Object Detection with Data Augmentation
  Jiawei Liang, Siyuan Liang^♠, Aishan Liu^♠, Ke Ma, Jingzhi Li, Xiaochun Cao
  ACM Multimedia (ACM MM), 2023.
  [Paper] [Code] (Oral)


• Faire: Repairing Fairness of Neural Networks via Neuron Condition Synthesis
  Tianlin Li, Xiaofei Xie, Jian Wang, Qing Guo Aishan Liu, Lei Ma, Yang Liu
  ACM Transactions on Software Engineering and Methodology (TOSEM), 2023.
  [Paper] [Code]


• Latent Imitator: Generating Natural Individual Discriminatory Instances for Black-Box Fairness Testing
  Yisong Xiao, Aishan Liu^♠, Tianlin Li, Xianglong Liu^♠
  ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA), 2023.
  [Paper] [Code]


• FAIRER: Fairness As Decision Rational Alignment
  Tianlin Li, Qing Guo, Aishan Liu, Mengnan Du, Zhiming Li, Yang Liu
  International Conference on Machine Learning (ICML), 2023.
  [Paper] [Code]


• Fairness via Group Contribution Matching
  Tianlin Li, Zhiming Li, Anran Li, Mengnan Du, Aishan Liu, Qing Guo, Guozhu Meng, Yang Liu
  International Joint Conference on Artificial Intelligence (IJCAI), 2023.
  [Paper] [Code]


• Exploring the Relationship between Architectural Design and Adversarially Robust Generalization
  Aishan Liu*, Shiyu Tang*, Siyuan Liang*, Ruihao Gong, Boxi Wu, Xianglong Liu, Dacheng Tao
  IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
  [Paper] [Code]


• Towards Benchmarking and Assessing Visual Naturalness of Physical World Adversarial Attacks
  Simin Li, Shuning Zhang, Gujun Chen, Dong Wang, Pu Feng, Jiakai Wang, Aishan Liu, Xin Yi, Xianglong Liu
  IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
  [Paper]


• SysNoise: Exploring and Benchmarking Training-Deployment System Inconsistency
  Yan Wang*, Yuhang Li*, Ruihao Gong*, Aishan Liu*, Yanfei Wang, Jian Hu, Yongqiang Yao, Yunchen Zhang, Tianzi Xiao, Fengwei Yu, Xianglong Liu
  Conference on Machine Learning and Systems (MLSys), 2023.
  [Paper] [Code]


• X-Adv: Physical Adversarial Object Attacks against X-ray Prohibited Item Detection
  Aishan Liu*, Jun Guo*, Jiakai Wang, Siyuan Liang, Renshuai Tao, Wenbo Zhou, Cong Liu, Xianglong Liu, Dacheng Tao
  USENIX Security Symposium (USENIX Security), 2023.
  [Paper] [Code]


• A Comprehensive Evaluation Framework for Deep Model Robustness
  Jun Guo, Wei Bao, Jiakai Wang, Yuqing Ma, Xinghai Gao, Gang Xiao, Aishan Liu^♠, Jian Dong, Xianglong Liu, Wenjun Wu
  Pattern Recognition (PR), 2023.
  [Paper] [Code]


• Improving Robust Fairness via Balance Adversarial Training
  Chunyu Sun, Chenye Xu, Chengyuan Yao, Siyuan Liang, Yichao Wu, Ding Liang, XiangLong Liu, Aishan Liu^♠
  AAAI Conference on Artificial Intelligence (AAAI), 2023.
  [Paper] [Code]



2022

• 面向深度强化学习的对抗攻防综述
  Aishan Liu, Jun Guo, Simin Li, Yisong Xiao, Xianglong Liu, Dacheng Tao
  计算机学报 (Chinese Journal of Computers), 2022.
  [Paper]


• 智能系统全生命周期安全测试理论与方法
  Jiakai Wang，Aishan Liu，Simin Li，Xianglong Liu, Wenjun Wu
  智能安全 (Artificial Intelligence Security), 2022.
  [Paper]


• Temporal Speciation Network for Few-Shot Object Detection
  Xiaowei Zhao, Xianglong Liu, Yuqing Ma, Shihao Bai, Yifan Shen, Zeyu Hao, Aishan Liu
  IEEE Transactions on Multimedia (IEEE TMM), 2022.
  [Paper] [Code]


• Harnessing Perceptual Adversarial Patches for Crowd Counting
  Shunchang Liu, Jiakai Wang, Aishan Liu^♠, Yingwei Li, Yijie Gao, Xianglong Liu, Dacheng Tao
  ACM Conference on Computer and Communications Security (ACM CCS), 2022.
  [Paper] [Code]


• Region-wise Generative Adversarial Image Inpainting for Large Missing Areas
  Yuqing Ma, Xianglong Liu, Shihao Bai, Aishan Liu, Dacheng Tao, Edwin Hancock
  IEEE Transactions on Cybernetics (IEEE TCYB), 2022.
  [Paper] [Code]


• Generating Transferable Adversarial Examples against Vision Transformers
  Yuxuan Wang, Jiakai Wang, Zixin Yin, Ruihao Gong, Jingyi Wang, Aishan Liu, Xianglong Liu
  ACM Multimedia (ACM MM), 2022.
  [Paper] [Code]


• Imitated Detectors: Stealing Knowledge of Black-box Object Detectors
  Siyuan Liang, Aishan Liu, Jiawei Liang, Longkang Li, Yang Bai, Xiaochun Cao
  ACM Multimedia (ACM MM), 2022.
  [Paper] [Code]


• Few-shot X-ray Prohibited Item Detection: A Benchmark and Weak-feature Enhancement Network
  Renshuai Tao, tianbo Wang, Ziyang Wu, Cong Liu, Aishan Liu, Xianglong Liu
  ACM Multimedia (ACM MM), 2022.
  [Paper] [Code]


• Defensive Patches for Robust Recognition in the Physical World
  Jiakai Wang, Zixin Yin, Pengfei Hu, Renshuai Tao, Haotong Qin, Xianglong Liu, Dacheng Tao, Aishan Liu
  IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
  [Paper] [Code]


• Exploring Endogenous Shift for Cross-domain Detection: A Large-scale Benchmark and Perturbation Suppression Network
  Renshuai Tao, Hainan Li, Tianbo Wang, Yanlu Wei, Yifu Ding, Bowei Jin, Hongping Zhi, Xianglong Liu, Aishan Liu
  IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
  [Paper]


• Revisiting Audio Visual Scene-Aware Dialog
  Aishan Liu, Huiyuan Xie, Xianglong Liu, Zixin Yin, Shunchang Liu
  NeuroComputing, 2022.
  [Paper]


• BIBERT: Accurate Fully Binarized BERT
  Haotong Qin, Yifu Ding, Mingyuan Zhang, Qinghua Yan, Aishan Liu, Qingqing Dang, Ziwei Liu, Xianglong Liu
  International Conference on Learning Representations (ICLR), 2022.
  [Paper] [Code]



2019-2021

• Universal Adversarial Patch Attack for Automatic Checkout using Perceptual and Attentional Bias
  Jiakai Wang*, Aishan Liu*, Xiao Bai, Xianglong Liu
  IEEE Transactions on Image Processing (IEEE TIP), 2021.
  [Paper] [Code]


• Progressive Diversified Augmentation for General Robustness of DNNs: A Unified Approach
  Hang Yu, Aishan Liu^♠, Gengchao Li, Jichen Yang, Chongzhi Zhang
  IEEE Transactions on Image Processing (IEEE TIP), 2021.
  [Paper] [Code]


• ARShoe: Real-Time Augmented Reality Shoe Try-on System on Smartphones
  Shan An, Guangfu Che, Jinghao Guo, Haogang Zhu, Junjie Ye, Fangru Zhou, Zhaoqi Zhu, Dong Wei, Aishan Liu, Wei Zhang
  ACM Multimedia (ACM MM), 2021.
  [Paper]


• On the Guaranteed Almost Equivalence Between Imitation Learning From Observation and Demonstration
  Zhihao Cheng, Liu Liu, Aishan Liu, Hao Sun, Meng Fang, Dacheng Tao
  IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS), 2021.
  [Paper]


• Training Robust Deep Neural Networks via Adversarial Noise Propagation
  Aishan Liu, Xianglong Liu, Hang Yu, Chongzhi Zhang, Qiang Liu, Dacheng Tao
  IEEE Transactions on Image Processing (IEEE TIP), 2021.
  [Paper] [Code]


• Dual Attention Suppression Attack: Generate Adversarial Camouflage in Physical World
  Jiakai Wang, Aishan Liu, Zixin Yin, Shunchang Liu, Shiyu Tang, Xianglong Liu
  IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
  [Paper] [Code] (Oral)


• Interpreting and Improving Adversarial Robustness of Deep Neural Networks with Neuron Sensitivity
  Chongzhi Zhang*, Aishan Liu*, Xianglong Liu, Yitao Xu, Hang Yu, Yuqing Ma, Tianlin Li
  IEEE Transactions on Image Processing (IEEE TIP), 2020.
  [Paper] [Code]


• Spatiotemporal Attacks for Embodied Agents
  Aishan Liu, Tairan Huang, Xianglong Liu, Yitao Xu, Yuqing Ma, Xinyun Chen, Stephen Maybank, Dacheng Tao
  European Conference on Computer Vision (ECCV), 2020.
  [Paper] [Code]


• Bias-based Universal Adversarial Patch Attack for Automatic Check-out
  Aishan Liu, Jiakai Wang, Xianglong Liu, Bowen Cao, Chongzhi Zhang, Hang Yu
  European Conference on Computer Vision (ECCV), 2020.
  [Paper] [Code]


• Understanding Adversarial Robustness via Critical Attacking Route
  Tianlin Li*, Aishan Liu*, Xianglong Liu, Yitao Xu, Chongzhi Zhang, Xiaofei Xie
  Information Sciences (INS), 2020.
  [Paper] [Code]


• 人工智能安全与评测
  刘艾杉, 王嘉凯, 刘祥龙
  人工智能 (AI-View), 2020.
  [Paper]


• 人工智能机器学习模型及系统的质量要素和测试方法
  王嘉凯, 刘艾杉, 刘祥龙
  信息技术与标准化, 2020.
  [Paper]


• Few-shot Visual Learning with Contextual Memory and Fine-grained Calibration
  Yuqing Ma, Shihao Bai, Wei Liu, Qingyu Zhang, Aishan Liu , Weimin Chen, Xianglong Liu
  International Joint Conference on Artificial Intelligence (IJCAI), 2020.
  [Paper]


• Transductive Relation-Propagation Network for Few-shot Learning
  Yuqing Ma, Xianglong Liu, Shihao Bai, Lei Wang, Dailan He, Aishan Liu
  International Joint Conference on Artificial Intelligence (IJCAI), 2020.
  [Paper] [Code]


• Coarse-to-Fine Image Inpainting via Region-wise Convolutions and Non-Local Correlation
  Haotong Qin, Yifu Ding, Mingyuan Zhang, Qinghua Yan, Aishan Liu, Qingqing Dang, Ziwei Liu, Xianglong Liu
  International Joint Conference on Artificial Intelligence (IJCAI), 2019.
  [Paper]


• Perceptual Sensitive GAN for Generating Adversarial Patches
  Aishan Liu, Xianglong Liu, Jiaxin Fan, Yuqing Ma, Anlan Zhang, Huiyuan Xie and Dacheng Tao
  AAAI Conference on Artificial Intelligence (AAAI), 2019.
  [Paper] (Spotlight)