Yehui Tang

According to our database, Yehui Tang authored at least 48 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

DenseMamba: State Space Models with Dense Hidden Connection for Efficient Large Language Models.

Wei He, Kai Han, Yehui Tang, Chengcheng Wang, Yujie Yang, Tianyu Guo, Yunhe Wang

CoRR, 2024

SAM-DiffSR: Structure-Modulated Diffusion Model for Image Super-Resolution.

Chengcheng Wang, Zhiwei Hao, Yehui Tang, Jianyuan Guo, Yujie Yang, Kai Han, Yunhe Wang

CoRR, 2024

A Survey on Transformer Compression.

Yehui Tang, Yunhe Wang, Jianyuan Guo, Zhijun Tu, Kai Han, Hailin Hu, Dacheng Tao

CoRR, 2024

Data-efficient Large Vision Models through Sequential Autoregression.

Jianyuan Guo, Zhiwei Hao, Chengcheng Wang, Yehui Tang, Han Wu, Han Hu, Kai Han, Chang Xu

CoRR, 2024

Rethinking Optimization and Architecture for Tiny Language Models.

Yehui Tang, Fangcheng Liu, Yunsheng Ni, Yuchuan Tian, Zheyuan Bai, Yi-Qi Hu, Sichao Liu, Shangling Jui, Kai Han, Yunhe Wang

CoRR, 2024

2023

A Survey on Vision Transformer.

Kai Han, Yunhe Wang, Hanting Chen, Xinghao Chen, Jianyuan Guo, Zhenhua Liu, Yehui Tang, An Xiao, Chunjing Xu, Yixing Xu, Zhaohui Yang, Yiman Zhang, Dacheng Tao

IEEE Trans. Pattern Anal. Mach. Intell., 2023

PanGu-π: Enhancing Language Model Architectures via Nonlinearity Compensation.

Yunhe Wang, Hanting Chen, Yehui Tang, Tianyu Guo, Kai Han, Ying Nie, Xutao Wang, Hailin Hu, Zheyuan Bai, Yun Wang, Fangcheng Liu, Zhicheng Liu, Jianyuan Guo, Sinan Zeng, Yinchen Zhang, Qinghua Xu, Qun Liu, Jun Yao, Chao Xu, Dacheng Tao

CoRR, 2023

TinySAM: Pushing the Envelope for Efficient Segment Anything Model.

Han Shu, Wenshuo Li, Yehui Tang, Yiman Zhang, Yihao Chen, Houqiang Li, Yunhe Wang, Xinghao Chen

CoRR, 2023

CBQ: Cross-Block Quantization for Large Language Models.

Xin Ding, Xiaoyu Liu, Yun Zhang, Zhijun Tu, Wei Li, Jie Hu, Hanting Chen, Yehui Tang, Zhiwei Xiong, Baoqun Yin, Yunhe Wang

CoRR, 2023

LightCLIP: Learning Multi-Level Interaction for Lightweight Vision-Language Models.

Ying Nie, Wei He, Kai Han, Yehui Tang, Tianyu Guo, Fanyi Du, Yunhe Wang

CoRR, 2023

One-for-All: Bridge the Gap Between Heterogeneous Architectures in Knowledge Distillation.

Zhiwei Hao, Jianyuan Guo, Kai Han, Yehui Tang, Han Hu, Yunhe Wang, Chang Xu

CoRR, 2023

GPT4Image: Can Large Pre-trained Models Help Vision Models on Perception Tasks?

Ning Ding, Yehui Tang, Zhongqian Fu, Chao Xu, Kai Han, Yunhe Wang

CoRR, 2023

One-for-All: Bridge the Gap Between Heterogeneous Architectures in Knowledge Distillation.

Zhiwei Hao, Jianyuan Guo, Kai Han, Yehui Tang, Han Hu, Yunhe Wang, Chang Xu

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Masked Image Modeling with Local Multi-Scale Reconstruction.

Haoqing Wang, Yehui Tang, Yunhe Wang, Jianyuan Guo, Zhi-Hong Deng, Kai Han

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Network Expansion For Practical Training Acceleration.

Ning Ding, Yehui Tang, Kai Han, Chao Xu, Yunhe Wang

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

Recent progress and perspectives on quantum computing for finance.

Yehui Tang, Junchi Yan, Guoqiang Hu, Baohua Zhang, Jinzan Zhou

Serv. Oriented Comput. Appl., 2022

FastMIM: Expediting Masked Image Modeling Pre-training for Vision.

Jianyuan Guo, Kai Han, Han Wu, Yehui Tang, Yunhe Wang, Chang Xu

CoRR, 2022

From Quantum Graph Computing to Quantum Graph Learning: A Survey.

Yehui Tang, Junchi Yan, Edwin R. Hancock

CoRR, 2022

PyramidTNT: Improved Transformer-in-Transformer Baselines with Pyramid Architecture.

Kai Han, Jianyuan Guo, Yehui Tang, Yunhe Wang

CoRR, 2022

GraphQNTK: Quantum Neural Tangent Kernel for Graph Data.

Yehui Tang, Junchi Yan

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

GhostNetV2: Enhance Cheap Operation with Long-Range Attention.

Yehui Tang, Kai Han, Jianyuan Guo, Chang Xu, Chao Xu, Yunhe Wang

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Learning Efficient Vision Transformers via Fine-Grained Manifold Distillation.

Zhiwei Hao, Jianyuan Guo, Ding Jia, Kai Han, Yehui Tang, Chao Zhang, Han Hu, Yunhe Wang

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Bridge the Gap Between Architecture Spaces via A Cross-Domain Predictor.

Yuqiao Liu, Yehui Tang, Zeqiong Lv, Yunhe Wang, Yanan Sun

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Vision GNN: An Image is Worth Graph of Nodes.

Kai Han, Yunhe Wang, Jianyuan Guo, Yehui Tang, Enhua Wu

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Towards a Native Quantum Paradigm for Graph Representation Learning: A Sampling-based Recurrent Embedding Approach.

Ge Yan, Yehui Tang, Junchi Yan

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Spatial-Channel Token Distillation for Vision MLPs.

Yanxi Li, Xinghao Chen, Minjing Dong, Yehui Tang, Yunhe Wang, Chang Xu

Proceedings of the International Conference on Machine Learning, 2022

An Image Patch is a Wave: Phase-Aware Vision MLP.

Yehui Tang, Kai Han, Jianyuan Guo, Chang Xu, Yanxi Li, Chao Xu, Yunhe Wang

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Patch Slimming for Efficient Vision Transformers.

Yehui Tang, Kai Han, Yunhe Wang, Chang Xu, Jianyuan Guo, Chao Xu, Dacheng Tao

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Hire-MLP: Vision MLP via Hierarchical Rearrangement.

Jianyuan Guo, Yehui Tang, Kai Han, Xinghao Chen, Han Wu, Chao Xu, Chang Xu, Yunhe Wang

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

CMT: Convolutional Neural Networks Meet Vision Transformers.

Jianyuan Guo, Kai Han, Han Wu, Yehui Tang, Xinghao Chen, Yunhe Wang, Chang Xu

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Source-Free Domain Adaptation via Distribution Estimation.

Ning Ding, Yixing Xu, Yehui Tang, Chao Xu, Yunhe Wang, Dacheng Tao

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

CMT: Convolutional Neural Networks Meet Vision Transformers.

Jianyuan Guo, Kai Han, Han Wu, Chang Xu, Yehui Tang, Chunjing Xu, Yunhe Wang

CoRR, 2021

Efficient Vision Transformers via Fine-Grained Manifold Distillation.

Ding Jia, Kai Han, Yunhe Wang, Yehui Tang, Jianyuan Guo, Chao Zhang, Dacheng Tao

CoRR, 2021

Visual Transformer Pruning.

Mingjian Zhu, Kai Han, Yehui Tang, Yunhe Wang

CoRR, 2021

Learning Frequency Domain Approximation for Binary Neural Networks.

Yixing Xu, Kai Han, Chang Xu, Yehui Tang, Chunjing Xu, Yunhe Wang

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Augmented Shortcuts for Vision Transformers.

Yehui Tang, Kai Han, Chang Xu, An Xiao, Yiping Deng, Chao Xu, Yunhe Wang

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Homogeneous Architecture Augmentation for Neural Predictor.

Yuqiao Liu, Yehui Tang, Yanan Sun

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

ReNAS: Relativistic Evaluation of Neural Architecture Search.

Yixing Xu, Yunhe Wang, Kai Han, Yehui Tang, Shangling Jui, Chunjing Xu, Chang Xu

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Manifold Regularized Dynamic Network Pruning.

Yehui Tang, Yunhe Wang, Yixing Xu, Yiping Deng, Chao Xu, Dacheng Tao, Chang Xu

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020

A Survey on Visual Transformer.

Kai Han, Yunhe Wang, Hanting Chen, Xinghao Chen, Jianyuan Guo, Zhenhua Liu, Yehui Tang, An Xiao, Chunjing Xu, Yixing Xu, Zhaohui Yang, Yiman Zhang, Dacheng Tao

CoRR, 2020

SCOP: Scientific Control for Reliable Neural Network Pruning.

Yehui Tang, Yunhe Wang, Yixing Xu, Dacheng Tao, Chunjing Xu, Chao Xu, Chang Xu

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

A Semi-Supervised Assessor of Neural Architectures.

Yehui Tang, Yunhe Wang, Yixing Xu, Hanting Chen, Boxin Shi, Chao Xu, Chunjing Xu, Qi Tian, Chang Xu

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Neuromorphic Camera Guided High Dynamic Range Imaging.

Jin Han, Chu Zhou, Peiqi Duan, Yehui Tang, Chang Xu, Chao Xu, Tiejun Huang, Boxin Shi

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Frequency Domain Compact 3D Convolutional Neural Networks.

Hanting Chen, Yunhe Wang, Han Shu, Yehui Tang, Chunjing Xu, Boxin Shi, Chao Xu, Qi Tian, Chang Xu

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Reborn Filters: Pruning Convolutional Neural Networks with Limited Data.

Yehui Tang, Shan You, Chang Xu, Jin Han, Chen Qian, Boxin Shi, Chao Xu, Changshui Zhang

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

Beyond Dropout: Feature Map Distortion to Regularize Deep Neural Networks.

Yehui Tang, Yunhe Wang, Yixing Xu, Boxin Shi, Chao Xu, Chunjing Xu, Chang Xu

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

RNAS: Architecture Ranking for Powerful Networks.

Yixing Xu, Yunhe Wang, Kai Han, Hanting Chen, Yehui Tang, Shangling Jui, Chunjing Xu, Qi Tian, Chang Xu

CoRR, 2019

Bringing Giant Neural Networks Down to Earth with Unlabeled Data.

Yehui Tang, Shan You, Chang Xu, Boxin Shi, Chao Xu

CoRR, 2019