Chen Zhu
Cited by
Cited by
Gemini: a family of highly capable multimodal models
G Team, R Anil, S Borgeaud, Y Wu, JB Alayrac, J Yu, R Soricut, ...
arXiv preprint arXiv:2312.11805, 2023
Freelb: Enhanced adversarial training for natural language understanding
C Zhu, Y Cheng, Z Gan, S Sun, T Goldstein, J Liu
ICLR 2020 & arXiv:1909.11764, 2020
Large-Scale Adversarial Training for Vision-and-Language Representation Learning
Z Gan, YC Chen, L Li, C Zhu, Y Cheng, J Liu
NeurIPS 2020 & arXiv:2006.06195, 2020
A field guide to federated optimization
J Wang, Z Charles, Z Xu, G Joshi, HB McMahan, M Al-Shedivat, G Andrew, ...
arXiv preprint arXiv:2107.06917, 2021
Transferable Clean-Label Poisoning Attacks on Deep Neural Nets
C Zhu, WR Huang, A Shafahi, H Li, G Taylor, C Studer, T Goldstein
ICML 2019 & arXiv: 1905.05897, 2019
The Intrinsic Dimension of Images and Its Impact on Learning
P Pope, C Zhu, A Abdelkader, M Goldblum, T Goldstein
ICLR 2021 & arXiv:2104.08894, 2021
Robust optimization as data augmentation for large-scale graphs
K Kong, G Li, M Ding, Z Wu, C Zhu, B Ghanem, G Taylor, T Goldstein
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022
Compressing neural networks using the variational information bottleneck
B Dai, C Zhu, B Guo, D Wipf
ICML 2018 & arXiv: 1802.10399, 2018
Certified defenses for adversarial patches
PY Chiang, R Ni, A Abdelkader, C Zhu, C Studor, T Goldstein
ICLR 2020 & arXiv:2003.06693, 2020
Adversarially robust transfer learning
A Shafahi, P Saadatpanah, C Zhu, A Ghiasi, C Studer, D Jacobs, ...
ICLR 2020 & arXiv:1905.08232, 2019
Deep k-NN Defense Against Clean-Label Data Poisoning Attacks
N Peri, N Gupta, WR Huang, L Fowl, C Zhu, S Feizi, T Goldstein, ...
Computer Vision–ECCV 2020 Workshops: Glasgow, UK, August 23–28, 2020 …, 2020
Structured attentions for visual question answering
C Zhu, Y Zhao, S Huang, K Tu, Y Ma
ICCV 2017 & arXiv: 1708.02071, 2017
Long-short transformer: Efficient transformers for language and vision
C Zhu, W Ping, C Xiao, M Shoeybi, T Goldstein, A Anandkumar, ...
NeurIPS 2021 & arXiv:2107.02192, 2021
Learning from Noisy Anchors for One-stage Object Detection
H Li, Z Wu, C Zhu, C Xiong, R Socher, LS Davis
CVPR 2020 & arXiv:1912.05086, 2019
Modifying memories in transformer models
C Zhu, AS Rawat, M Zaheer, S Bhojanapalli, D Li, F Yu, S Kumar
arXiv preprint arXiv:2012.00363, 2020
Learning visual knowledge memory networks for visual question answering
Z Su, C Zhu, Y Dong, D Cai, Y Chen, J Li
CVPR 2018 & arXiv: 1806.04860, 2018
GradInit: Learning to initialize neural networks for stable and efficient training
C Zhu, R Ni, Z Xu, K Kong, WR Huang, T Goldstein
NeurIPS 2021 & arXiv:2102.08098, 2021
Fine-grained video categorization with redundancy reduction attention
C Zhu, X Tan, F Zhou, X Liu, K Yue, E Ding, Y Ma
Proceedings of the European Conference on Computer Vision (ECCV), 136-152, 2018
Retrieval meets long context large language models
P Xu, W Ping, X Wu, L McAfee, C Zhu, Z Liu, S Subramanian, ...
ICLR 2024 & arXiv:2310.03025, 2023
Pre-Train Your Loss: Easy Bayesian Transfer Learning with Informative Priors
R Shwartz-Ziv, M Goldblum, H Souri, S Kapoor, C Zhu, Y LeCun, ...
NeurIPS 2022 & arXiv:2205.10279, 2022
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