Wenqi Shao
Wenqi Shao
Researcher at Shanghai AI Laboratory
Verified email at - Homepage
Cited by
Cited by
Towards Understanding Regularization in Batch Normalization
P Luo*, X Wang*, W Shao*, Z Peng (*Equal Contribution)
ICLR 2019, 2018
Gpt4roi: Instruction tuning large language model on region-of-interest
S Zhang, P Sun, S Chen, M Xiao, W Shao, W Zhang, K Chen, P Luo
arXiv preprint arXiv:2307.03601, 2023
Lvlm-ehub: A comprehensive evaluation benchmark for large vision-language models
P Xu, W Shao, K Zhang, P Gao, S Liu, M Lei, F Meng, S Huang, Y Qiao, ...
arXiv preprint arXiv:2306.09265, 2023
Sphinx: The joint mixing of weights, tasks, and visual embeddings for multi-modal large language models
Z Lin, C Liu, R Zhang, P Gao, L Qiu, H Xiao, H Qiu, C Lin, W Shao, ...
arXiv preprint arXiv:2311.07575, 2023
What makes for end-to-end object detection?
P Sun, Y Jiang, E Xie, W Shao, Z Yuan, C Wang, P Luo
International Conference on Machine Learning, 9934-9944, 2021
SSN: Learning Sparse Switchable Normalization via SparsestMax
W Shao, J Li, J Ren, R Zhang, X Wang, P Luo
International Journal of Computer Vision, 2019
SSN: Learning Sparse Switchable Normalization via SparsestMax
W Shao*, T Meng*, J Li, R Zhang, Y Li, X Wang, ...
CVPR 2019, arXiv preprint arXiv:1903.03793, 2019
Omniquant: Omnidirectionally calibrated quantization for large language models
W Shao, M Chen, Z Zhang, P Xu, L Zhao, Z Li, K Zhang, P Gao, Y Qiao, ...
arXiv preprint arXiv:2308.13137, 2023
Imagebind-llm: Multi-modality instruction tuning
J Han, R Zhang, W Shao, P Gao, P Xu, H Xiao, K Zhang, C Liu, S Wen, ...
arXiv preprint arXiv:2309.03905, 2023
Rethinking the pruning criteria for convolutional neural network
Z Huang, W Shao, X Wang, L Lin, P Luo
Advances in Neural Information Processing Systems 34, 16305-16318, 2021
Differentiable Learning-to-Group Channels via Groupable Convolutional Neural Networks
Z Zhaoyang, L Jingyu, S Wenqi, P Zhanglin, Z Ruimao, W Xiaogang, ...
ICCV 2019, 2019
Sphinx-x: Scaling data and parameters for a family of multi-modal large language models
P Gao, R Zhang, C Liu, L Qiu, S Huang, W Lin, S Zhao, S Geng, Z Lin, ...
arXiv preprint arXiv:2402.05935, 2024
Differentiable Dynamic Quantization with Mixed Precision and Adaptive Resolution
Z Zhaoyang, S Wenqi, G Jinwei, W Xiaogang, L Ping
ICML 2021, 2021
Differentiable Dynamic Normalization for Learning Deep Representation
P Luo, P Zhanglin, S Wenqi, Z Ruimao, R Jiamin, W Lingyun
ICML 2019,, 2019
Learning Efficient Detector with Semi-supervised Adaptive Distillation
S Tang, L Feng, W Shao, Z Kuang, W Zhang, Y Chen
BMVC 2019, arXiv preprint arXiv:1901.00366, 2019
Tiny lvlm-ehub: Early multimodal experiments with bard
W Shao, Y Hu, P Gao, M Lei, K Zhang, F Meng, P Xu, S Huang, H Li, ...
arXiv preprint arXiv:2308.03729, 2023
Not All Models Are Equal: Predicting Model Transferability in a Self-challenging Fisher Space
W Shao, X Zhao, Y Ge, Z Zhang, L Yang, X Wang, Y Shan, P Luo
ECCV 2022, arXiv preprint arXiv:2207.03036, 2022
Convolution-weight-distribution assumption: Rethinking the criteria of channel pruning
Z Huang*, W Shao*, X Wang, L Lin, P Luo
NeurIPS 2021, arXiv preprint arXiv:2004.11627, 2020
DiffRate: Differentiable Compression Rate for Efficient Vision Transformers
M Chen, W Shao, P Xu, M Lin, K Zhang, F Chao, R Ji, Y Qiao, P Luo
ICCV23, arXiv preprint arXiv:2305.17997, 2023
Channel equilibrium networks for learning deep representation
W Shao, S Tang, X Pan, P Tan, X Wang, P Luo
ICML 2020, arXiv preprint arXiv:2003.00214, 2020
The system can't perform the operation now. Try again later.
Articles 1–20