| 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 | 96 | 2024 |
| Randomized adversarial training via taylor expansion G Jin, X Yi, D Wu, R Mu, X Huang Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2023 | 50 | 2023 |
| Position: Building Guardrails for Large Language Models Requires Systematic Design D Yi*, R Mu*, G Jin, Y Qi, J Hu, X Zhao, J Meng, W Ruan, X Huang Forty-first International Conference on Machine Learning, 2024 | 43* | 2024 |
| Sparse adversarial video attacks with spatial transformations R Mu, W Ruan, LS Marcolino, Q Ni The British Machine Vision Conference (BMVC)，2021, 2021 | 24 | 2021 |
| Safeguarding Large Language Models: A Survey Y Dong*, R Mu*, Y Zhang, S Sun, T Zhang, C Wu, G Jin, Y Qi, J Hu, ... arXiv preprint arXiv:2406.02622, 2024 | 16 | 2024 |
| Certified Policy Smoothing for Cooperative Multi-Agent Reinforcement Learning R Mu, W Ruan, LS Marcolino, G Jin, Q Ni AAAI 2023, 2022 | 15 | 2022 |
| 3DVerifier: efficient robustness verification for 3D point cloud models R Mu, W Ruan, LS Marcolino, Q Ni Machine Learning 113 (4), 1771-1798, 2024 | 14 | 2024 |
| Enhancing robustness in video recognition models: Sparse adversarial attacks and beyond R Mu, L Marcolino, Q Ni, W Ruan Neural Networks 171, 127-143, 2024 | 8* | 2024 |
| Reward Certification for Policy Smoothed Reinforcement Learning R Mu, LS Marcolino, T Zhang, Y Zhang, X Huang, W Ruan AAAI, 2024, 2023 | 5 | 2023 |
| Towards fairness-aware adversarial learning Y Zhang, T Zhang, R Mu, X Huang, W Ruan Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | 4 | 2024 |
| Nrat: towards adversarial training with inherent label noise Z Chen, F Wang, R Mu, P Xu, X Huang, W Ruan Machine Learning 113 (6), 3589-3610, 2024 | 2 | 2024 |
| Enhancing Robust Fairness via Confusional Spectral Regularization G Jin, S Wu, J Liu, T Huang, R Mu arXiv preprint arXiv:2501.13273, 2025 | 1 | 2025 |
| Position: building guardrails for large language models requires systematic design Y Dong, R Mu, G Jin, Y Qi, J Hu, X Zhao, J Meng, W Ruan, X Huang International Conference on Machine Learning, 11375-11394, 2024 | 1 | 2024 |
| Invariant Correlation of Representation with Label G Jin, R Mu, X Yi, X Huang, L Zhang arXiv preprint arXiv:2407.01749, 2024 | | 2024 |
| DeepGRE: Global Robustness Evaluation of Deep Neural Networks T Zhang, J Liu, Y Zhang, R Mu, W Ruan ICASSP 2024-2024 IEEE International Conference on Acoustics, Speech and …, 2024 | | 2024 |
| PRASS: Probabilistic Risk-averse Robust Learning with Stochastic Search T Zhang, Y Zhang, R Mu, J Liu, J Fieldsend, W Ruan International Joint Conference on Artificial Intelligence, 559-567, 2024 | | 2024 |
| Assessment of the Robustness of Deep Neural Networks (DNNS) R Mu PQDT-Global, 2023 | | 2023 |
| Beyond Levels and Continuity: A New Statistical Method for DNNs Robustness Evaluation Y Zhang, F Wang, T Zhang, R Mu, X Huang, W Ruan | | |
Xiaowei HuangProfessor of Computer Science, University of LiverpoolВерификована је имејл адреса на liverpool.ac.uk