| Backdoor Scanning for Deep Neural Networks through K-Arm Optimization. G Shen, Y Liu, G Tao, S An, Q Xu, S Cheng, S Ma, X Zhang ICML 2021, 2021 | 126 | 2021 |
| Piccolo: Exposing complex backdoors in nlp transformer models Y Liu, G Shen, G Tao, S An, S Ma, X Zhang 2022 IEEE Symposium on Security and Privacy (SP), 2025-2042, 2022 | 89 | 2022 |
| Better trigger inversion optimization in backdoor scanning G Tao, G Shen, Y Liu, S An, Q Xu, S Ma, P Li, X Zhang Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 87 | 2022 |
| Complex backdoor detection by symmetric feature differencing Y Liu, G Shen, G Tao, Z Wang, S Ma, X Zhang Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 77* | 2022 |
| Mirror: Model inversion for deep learning network with high fidelity S An, G Tao, Q Xu, Y Liu, G Shen, Y Yao, J Xu, X Zhang Proceedings of the 29th Network and Distributed System Security Symposium, 2022 | 63 | 2022 |
| Detecting backdoors in pre-trained encoders S Feng, G Tao, S Cheng, G Shen, X Xu, Y Liu, K Zhang, S Ma, X Zhang Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 59 | 2023 |
| Model orthogonalization: Class distance hardening in neural networks for better security G Tao, Y Liu, G Shen, Q Xu, S An, Z Zhang, X Zhang 2022 IEEE Symposium on Security and Privacy (SP), 1372-1389, 2022 | 56 | 2022 |
| Flip: A provable defense framework for backdoor mitigation in federated learning K Zhang, G Tao, Q Xu, S Cheng, S An, Y Liu, S Feng, G Shen, PY Chen, ... arXiv preprint arXiv:2210.12873, 2022 | 52 | 2022 |
| Constrained optimization with dynamic bound-scaling for effective nlp backdoor defense G Shen, Y Liu, G Tao, Q Xu, Z Zhang, S An, S Ma, X Zhang International Conference on Machine Learning, 19879-19892, 2022 | 50 | 2022 |
| On large language models’ resilience to coercive interrogation Z Zhang, G Shen, G Tao, S Cheng, X Zhang 2024 IEEE Symposium on Security and Privacy (SP), 826-844, 2024 | 32* | 2024 |
| Distribution preserving backdoor attack in self-supervised learning G Tao, Z Wang, S Feng, G Shen, S Ma, X Zhang 2024 IEEE Symposium on Security and Privacy (SP), 2029-2047, 2024 | 25 | 2024 |
| Elijah: Eliminating backdoors injected in diffusion models via distribution shift S An, SY Chou, K Zhang, Q Xu, G Tao, G Shen, S Cheng, S Ma, PY Chen, ... Proceedings of the AAAI Conference on Artificial Intelligence 38 (10), 10847 …, 2024 | 25* | 2024 |
| Penet: object detection using points estimation in aerial images Z Tang, X Liu, G Shen, B Yang arXiv preprint arXiv:2001.08247, 2020 | 22 | 2020 |
| Improving binary code similarity transformer models by semantics-driven instruction deemphasis X Xu, S Feng, Y Ye, G Shen, Z Su, S Cheng, G Tao, Q Shi, Z Zhang, ... Proceedings of the 32nd ACM SIGSOFT International Symposium on Software …, 2023 | 21* | 2023 |
| Brain tumor segmentation using concurrent fully convolutional networks and conditional random fields G Shen, Y Ding, T Lan, H Chen, Z Qin Proceedings of the 3rd International Conference on Multimedia and Image …, 2018 | 17 | 2018 |
| Parafuzz: An interpretability-driven technique for detecting poisoned samples in nlp L Yan, Z Zhang, G Tao, K Zhang, X Chen, G Shen, X Zhang Advances in Neural Information Processing Systems 36, 66755-66767, 2023 | 16 | 2023 |
| Beagle: Forensics of deep learning backdoor attack for better defense S Cheng, G Tao, Y Liu, S An, X Xu, S Feng, G Shen, K Zhang, Q Xu, S Ma, ... arXiv preprint arXiv:2301.06241, 2023 | 15 | 2023 |
| Backdoor vulnerabilities in normally trained deep learning models G Tao, Z Wang, S Cheng, S Ma, S An, Y Liu, G Shen, Z Zhang, Y Mao, ... arXiv preprint arXiv:2211.15929, 2022 | 15 | 2022 |
| Rapid optimization for jailbreaking llms via subconscious exploitation and echopraxia G Shen, S Cheng, K Zhang, G Tao, S An, L Yan, Z Zhang, S Ma, X Zhang arXiv preprint arXiv:2402.05467, 2024 | 14 | 2024 |
| Advspade: Realistic unrestricted attacks for semantic segmentation G Shen, C Mao, J Yang, B Ray arXiv preprint arXiv:1910.02354, 2019 | 13 | 2019 |
Xiangyu ZhangSamuel Conte Professor of Computer Science, Purdue UniversityPreverjeni e-poštni naslov na cs.purdue.edu