| Baylime: Bayesian local interpretable model-agnostic explanations X Zhao, W Huang, X Huang, V Robu, D Flynn Uncertainty in artificial intelligence, 887-896, 2021 | 114 | 2021 |
| A survey of safety and trustworthiness of large language models through the lens of verification and validation X Huang, W Ruan, W Huang, G Jin, Y Dong, C Wu, S Bensalem, R Mu, ... Artificial Intelligence Review 57 (7), 175, 2024 | 94 | 2024 |
| Coverage-guided testing for recurrent neural networks W Huang, Y Sun, X Zhao, J Sharp, W Ruan, J Meng, X Huang IEEE Transactions on Reliability 71 (3), 1191-1206, 2021 | 69* | 2021 |
| Enhancing adversarial training with second-order statistics of weights G Jin, X Yi, W Huang, S Schewe, X Huang Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022 | 66 | 2022 |
| Assessing the Reliability of Deep Learning Classifiers Through Robustness Evaluation and Operational Profiles X Zhao, W Huang, A Banks, V Cox, D Flynn, S Schewe, X Huang AISafety'21: Workshop on AI Safety at IJCAI-21, 2021 | 32* | 2021 |
| Reliability assessment and safety arguments for machine learning components in system assurance Y Dong, W Huang, V Bharti, V Cox, A Banks, S Wang, X Zhao, S Schewe, ... ACM Transactions on Embedded Computing Systems 22 (3), 1-48, 2023 | 31* | 2023 |
| SAFARI: Versatile and Efficient Evaluations for Robustness of Interpretability W Huang, X Zhao, G Jin, X Huang Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), 2023 | 28 | 2023 |
| A Simple Framework to Enhance the Adversarial Robustness of Deep Learning-based Intrusion Detection System X Yuan, S Han, W Huang, H Ye, X Kong, F Zhang Computers & Security, 2023 | 17 | 2023 |
| Embedding and extraction of knowledge in tree ensemble classifiers W Huang, X Zhao, X Huang Machine Learning 111 (5), 1925-1958, 2022 | 13 | 2022 |
| Hierarchical Distribution-Aware Testing of Deep Learning W Huang, X Zhao, A Banks, V Cox, X Huang ACM Transactions on Software Engineering and Methodology, 2023 | 11 | 2023 |
| Detecting operational adversarial examples for reliable deep learning X Zhao, W Huang, S Schewe, Y Dong, X Huang 2021 51st Annual IEEE/IFIP International Conference on Dependable Systems …, 2021 | 11 | 2021 |
| What, Indeed, is an Achievable Provable Guarantee for Learning-Enabled Safety Critical Systems S Bensalem, CH Cheng, W Huang, X Huang, C Wu, X Zhao ISoLA'23: Int. Symp. on Leveraging Applications of Formal Methods …, 2023 | 9 | 2023 |
| Practical verification of neural network enabled state estimation system for robotics W Huang, Y Zhou, Y Sun, J Sharp, S Maskell, X Huang 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2020 | 9 | 2020 |
| A Hierarchical HAZOP-Like Safety Analysis for Learning-Enabled Systems Y Qi, PR Conmy, W Huang, X Zhao, X Huang AISafety'22: Workshop on AI Safety at IJCAI-22, 2022 | 8 | 2022 |
| Tutorials on testing neural networks N Berthier, Y Sun, W Huang, Y Zhang, W Ruan, X Huang arXiv preprint arXiv:2108.01734, 2021 | 8 | 2021 |
| Formal Verification of Robustness and Resilience of Learning-Enabled State Estimation Systems W Huang, Y Zhou, G Jin, Y Sun, J Meng, F Zhang, X Huang Neurocomputing, 2024 | 6* | 2024 |
| Diversity supporting robustness: Enhancing adversarial robustness via differentiated ensemble predictions X Chen, W Huang, Z Peng, W Guo, F Zhang Computers & Security 142, 103861, 2024 | 2 | 2024 |
| Ensemble Adversarial Defense via Integration of Multiple Dispersed Low Curvature Models K Zhao, X Chen, W Huang, L Ding, X Kong, F Zhang 2024 International Joint Conference on Neural Networks (IJCNN), 2024 | 2 | 2024 |
| Adversarial defence by learning differentiated feature representation in deep ensemble X Chen, W Huang, W Guo, F Zhang, J Du, Z Zhou Machine Vision and Applications 35 (4), 88, 2024 | 1 | 2024 |
| Fortifying graph neural networks against adversarial attacks via ensemble learning C Zhou, W Huang, X Miao, Y Peng, X Kong, Y Cao, X Chen Knowledge-Based Systems 309, 112867, 2025 | | 2025 |
Xiaowei HuangProfessor of Computer Science, University of LiverpoolVerified email at liverpool.ac.uk