| Neural attention distillation: Erasing backdoor triggers from deep neural networks Y Li, X Lyu, N Koren, L Lyu, B Li, X Ma ICLR 2021, 2021 | 410 | 2021 |
| Anti-backdoor learning: Training clean models on poisoned data Y Li, X Lyu, N Koren, L Lyu, B Li, X Ma NeurIPS 2021, 2021 | 274 | 2021 |
| Reconstructive Neuron Pruning for Backdoor Defense Y Li, X Lyu, X Ma, N Koren, L Lyu, B Li, YG Jiang ICML 2023, 2023 | 25 | 2023 |
| Defending Large Language Models Against Jailbreak Attacks via Layer-specific Editing W Zhao, Z Li, Y Li, Y Zhang, J Sun arXiv preprint arXiv:2405.18166, 2024 | 5 | 2024 |
| Multi-Trigger Backdoor Attacks: More Triggers, More Threats Y Li, X Ma, J He, H Huang, YG Jiang arXiv preprint arXiv:2401.15295, 2024 | 4 | 2024 |
| End-to-End Anti-Backdoor Learning on Images and Time Series Y Jiang, X Ma, SM Erfani, Y Li, J Bailey arXiv preprint arXiv:2401.03215, 2024 | 1 | 2024 |
| BackdoorLLM: A Comprehensive Benchmark for Backdoor Attacks on Large Language Models Y Li, H Huang, Y Zhao, X Ma, J Sun arXiv preprint arXiv:2408.12798, 2024 | | 2024 |
Xingjun MaSchool of Computer Science, Fudan University在 unimelb.edu.au 的电子邮件经过验证
