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Tianyu Pang
Tianyu Pang
Senior Research Scientist, Sea AI Lab
Подтвержден адрес электронной почты в домене sea.com - Главная страница
Название
Процитировано
Процитировано
Год
Boosting adversarial attacks with momentum
Y Dong, F Liao, T Pang, H Su, J Zhu, X Hu, J Li
IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2018), 2018
34342018
Defense against adversarial attacks using high-level representation guided denoiser
F Liao, M Liang, Y Dong, T Pang, X Hu, J Zhu
IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2018), 2018
10892018
Evading defenses to transferable adversarial examples by translation-invariant attacks
Y Dong, T Pang, H Su, J Zhu
IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2019), 2019
10252019
Improving adversarial robustness via promoting ensemble diversity
T Pang, K Xu, C Du, N Chen, J Zhu
International Conference on Machine Learning (ICML 2019), 2019
5212019
Adversarial attacks and defences competition
A Kurakin, I Goodfellow, S Bengio, Y Dong, F Liao, M Liang, T Pang, ...
The NIPS'17 Competition: Building Intelligent Systems, 195-231, 2018
3952018
Benchmarking adversarial robustness on image classification
Y Dong, QA Fu, X Yang, T Pang, H Su, Z Xiao, J Zhu
IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2020), 2020
3382020
Bag of tricks for adversarial training
T Pang, X Yang, Y Dong, H Su, J Zhu
International Conference on Learning Representations (ICLR 2021), 2021
3092021
Improving black-box adversarial attacks with a transfer-based prior
S Cheng, Y Dong, T Pang, H Su, J Zhu
Annual Conference on Neural Information Processing Systems (NeurIPS 2019), 2019
3032019
Towards robust detection of adversarial examples
T Pang, C Du, Y Dong, J Zhu
Annual Conference on Neural Information Processing Systems (NeurIPS 2018), 2018
270*2018
Better diffusion models further improve adversarial training
Z Wang*, T Pang*, C Du, M Lin, W Liu, S Yan
International Conference on Machine Learning (ICML 2023), 2023
2422023
Rethinking softmax cross-entropy loss for adversarial robustness
T Pang, K Xu, Y Dong, C Du, N Chen, J Zhu
International Conference on Learning Representations (ICLR 2020), 2020
2082020
On evaluating adversarial robustness of large vision-language models
Y Zhao*, T Pang*, C Du, X Yang, C Li, NM Cheung, M Lin
Annual Conference on Neural Information Processing Systems (NeurIPS 2023), 2023
1842023
Boosting adversarial training with hypersphere embedding
T Pang, X Yang, Y Dong, K Xu, H Su, J Zhu
Annual Conference on Neural Information Processing Systems (NeurIPS 2020), 2020
1702020
Lorahub: Efficient cross-task generalization via dynamic lora composition
C Huang, Q Liu, BY Lin, T Pang, C Du, M Lin
Conference on Language Modeling (COLM 2024), 2024
1542024
Robustness and Accuracy Could Be Reconcilable by (Proper) Definition
T Pang, M Lin, X Yang, J Zhu, S Yan
International Conference on Machine Learning (ICML 2022), 2022
1512022
Mixup inference: Better exploiting mixup to defend adversarial attacks
T Pang, K Xu, J Zhu
International Conference on Learning Representations (ICLR 2020), 2020
1412020
Adversarial Distributional Training for Robust Deep Learning
Z Deng, Y Dong, T Pang, H Su, J Zhu
Annual Conference on Neural Information Processing Systems (NeurIPS 2020), 2020
1402020
Black-box Detection of Backdoor Attacks with Limited Information and Data
Y Dong, X Yang, Z Deng, T Pang, Z Xiao, H Su, J Zhu
International Conference on Computer Vision (ICCV 2021), 2021
1362021
A recipe for watermarking diffusion models
Y Zhao, T Pang, C Du, X Yang, NM Cheung, M Lin
arXiv preprint arXiv:2303.10137, 2023
1242023
Towards face encryption by generating adversarial identity masks
X Yang, Y Dong, T Pang, J Zhu, H Su
International Conference on Computer Vision (ICCV 2021), 2021
1092021
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