Zhihang Yuan

According to our database, Zhihang Yuan authored at least 44 papers between 2017 and 2024.

Collaborative distances:

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

2024

Latency-Aware Unified Dynamic Networks for Efficient Image Recognition.

Yizeng Han, Zeyu Liu, Zhihang Yuan, Yifan Pu, Chaofei Wang, Shiji Song, Gao Huang

IEEE Trans. Pattern Anal. Mach. Intell., December, 2024

Post-training quantization for re-parameterization via coarse & fine weight splitting.

Dawei Yang, Ning He, Xing Hu, Zhihang Yuan, Jiangyong Yu, Chen Xu, Zhe Jiang

J. Syst. Archit., February, 2024

Stabilized activation scale estimation for precise Post-Training Quantization.

Zhenyang Hao, Xinggang Wang, Jiawei Liu, Zhihang Yuan, Dawei Yang, Wenyu Liu

Neurocomputing, February, 2024

CSKV: Training-Efficient Channel Shrinking for KV Cache in Long-Context Scenarios.

Luning Wang, Shiyao Li, Xuefei Ning, Zhihang Yuan, Shengen Yan, Guohao Dai, Yu Wang

CoRR, 2024

DiTFastAttn: Attention Compression for Diffusion Transformer Models.

Zhihang Yuan, Pu Lu, Hanling Zhang, Xuefei Ning, Linfeng Zhang, Tianchen Zhao, Shengen Yan, Guohao Dai, Yu Wang

CoRR, 2024

PillarHist: A Quantization-aware Pillar Feature Encoder based on Height-aware Histogram.

Sifan Zhou, Zhihang Yuan, Dawei Yang, Xubin Wen, Xing Hu, Yuguang Shi, Ziyu Zhao, Xiaobo Lu

CoRR, 2024

I-LLM: Efficient Integer-Only Inference for Fully-Quantized Low-Bit Large Language Models.

Xing Hu, Yuan Cheng, Dawei Yang, Zhihang Yuan, Jiangyong Yu, Chen Xu, Sifan Zhou

CoRR, 2024

A Closer Look at Time Steps is Worthy of Triple Speed-Up for Diffusion Model Training.

Kai Wang, Yukun Zhou, Mingjia Shi, Zhihang Yuan, Yuzhang Shang, Xiaojiang Peng, Hanwang Zhang, Yang You

CoRR, 2024

SKVQ: Sliding-window Key and Value Cache Quantization for Large Language Models.

Haojie Duanmu, Zhihang Yuan, Xiuhong Li, Jiangfei Duan, Xingcheng Zhang, Dahua Lin

CoRR, 2024

A Survey on Efficient Inference for Large Language Models.

Zixuan Zhou, Xuefei Ning, Ke Hong, Tianyu Fu, Jiaming Xu, Shiyao Li, Yuming Lou, Luning Wang, Zhihang Yuan, Xiuhong Li, Shengen Yan, Guohao Dai, Xiao-Ping Zhang, Yuhan Dong, Yu Wang

CoRR, 2024

PillarTrack: Redesigning Pillar-based Transformer Network for Single Object Tracking on Point Clouds.

Weisheng Xu, Sifan Zhou, Zhihang Yuan

CoRR, 2024

LLM Inference Unveiled: Survey and Roofline Model Insights.

Zhihang Yuan, Yuzhang Shang, Yang Zhou, Zhen Dong, Zhe Zhou, Chenhao Xue, Bingzhe Wu, Zhikai Li, Qingyi Gu, Yong Jae Lee, Yan Yan, Beidi Chen, Guangyu Sun, Kurt Keutzer

CoRR, 2024

WKVQuant: Quantizing Weight and Key/Value Cache for Large Language Models Gains More.

Yuxuan Yue, Zhihang Yuan, Haojie Duanmu, Sifan Zhou, Jianlong Wu, Liqiang Nie

CoRR, 2024

QuEST: Low-bit Diffusion Model Quantization via Efficient Selective Finetuning.

Haoxuan Wang, Yuzhang Shang, Zhihang Yuan, Junyi Wu, Yan Yan

CoRR, 2024

34.3 A 22nm 64kb Lightning-Like Hybrid Computing-in-Memory Macro with a Compressed Adder Tree and Analog-Storage Quantizers for Transformer and CNNs.

An Guo, Xi Chen, Fangyuan Dong, Jinwu Chen, Zhihang Yuan, Xing Hu, Yuanpeng Zhang, Jingmin Zhang, Yuchen Tang, Zhican Zhang, Gang Chen, Dawei Yang, Zhaoyang Zhang, Lizheng Ren, Tianzhu Xiong, Bo Wang, Bo Liu, Weiwei Shan, Xinning Liu, Hao Cai, Guangyu Sun, Jun Yang, Xin Si

Proceedings of the IEEE International Solid-State Circuits Conference, 2024

Learning High-Frequency Functions Made Easy with Sinusoidal Positional Encoding.

Chuanhao Sun, Zhihang Yuan, Kai Xu, Luo Mai, N. Siddharth, Shuo Chen, Mahesh K. Marina

Proceedings of the Forty-first International Conference on Machine Learning, 2024

PB-LLM: Partially Binarized Large Language Models.

Zhihang Yuan, Yuzhang Shang, Zhen Dong

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Algorithm-Hardware Co-Design for Energy-Efficient A/D Conversion in ReRAM-Based Accelerators.

Chenguang Zhang, Zhihang Yuan, Xingchen Li, Guangyu Sun

Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2024

2023

FD-CNN: A Frequency-Domain FPGA Acceleration Scheme for CNN-Based Image-Processing Applications.

Xiaoyang Wang, Zhe Zhou, Zhihang Yuan, Jingchen Zhu, Yulong Cao, Yao Zhang, Kangrui Sun, Guangyu Sun

ACM Trans. Embed. Comput. Syst., November, 2023

ASVD: Activation-aware Singular Value Decomposition for Compressing Large Language Models.

Zhihang Yuan, Yuzhang Shang, Yue Song, Qiang Wu, Yan Yan, Guangyu Sun

CoRR, 2023

PB-LLM: Partially Binarized Large Language Models.

Yuzhang Shang, Zhihang Yuan, Qiang Wu, Zhen Dong

CoRR, 2023

Improving Post-Training Quantization on Object Detection with Task Loss-Guided Lp Metric.

Lin Niu, Jiawei Liu, Zhihang Yuan, Dawei Yang, Xinggang Wang, Wenyu Liu

CoRR, 2023

RPTQ: Reorder-based Post-training Quantization for Large Language Models.

Zhihang Yuan, Lin Niu, Jiawei Liu, Wenyu Liu, Xinggang Wang, Yuzhang Shang, Guangyu Sun, Qiang Wu, Jiaxiang Wu, Bingzhe Wu

CoRR, 2023

Benchmarking the Reliability of Post-training Quantization: a Particular Focus on Worst-case Performance.

Zhihang Yuan, Jiawei Liu, Jiaxiang Wu, Dawei Yang, Qiang Wu, Guangyu Sun, Wenyu Liu, Xinggang Wang, Bingzhe Wu

CoRR, 2023

MIM4DD: Mutual Information Maximization for Dataset Distillation.

Yuzhang Shang, Zhihang Yuan, Yan Yan

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

Post-Training Quantization on Diffusion Models.

Yuzhang Shang, Zhihang Yuan, Bin Xie, Bingzhe Wu, Yan Yan

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

PD-Quant: Post-Training Quantization Based on Prediction Difference Metric.

Jiawei Liu, Lin Niu, Zhihang Yuan, Dawei Yang, Xinggang Wang, Wenyu Liu

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

2022

Flatfish: A Reinforcement Learning Approach for Application-Aware Address Mapping.

Xingchen Li, Zhihang Yuan, Yijin Guan, Guangyu Sun, Tao Zhang, Rongshan Wei, Dimin Niu

IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2022

Latency-aware Spatial-wise Dynamic Networks.

Yizeng Han, Zhihang Yuan, Yifan Pu, Chenhao Xue, Shiji Song, Guangyu Sun, Gao Huang

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

Enabling High-Quality Uncertainty Quantification in a PIM Designed for Bayesian Neural Network.

Xingchen Li, Bingzhe Wu, Guangyu Sun, Zhe Zhang, Zhihang Yuan, Runsheng Wang, Ru Huang, Dimin Niu, Hongzhong Zheng, Zhichao Lu, Liang Zhao, Meng-Fan Marvin Chang, Tianchan Guan, Xin Si

Proceedings of the IEEE International Symposium on High-Performance Computer Architecture, 2022

PTQ4ViT: Post-training Quantization for Vision Transformers with Twin Uniform Quantization.

Zhihang Yuan, Chenhao Xue, Yiqi Chen, Qiang Wu, Guangyu Sun

Proceedings of the Computer Vision - ECCV 2022, 2022

Tailor: removing redundant operations in memristive analog neural network accelerators.

Xingchen Li, Zhihang Yuan, Guangyu Sun, Liang Zhao, Zhichao Lu

Proceedings of the DAC '22: 59th ACM/IEEE Design Automation Conference, San Francisco, California, USA, July 10, 2022

2021

PTQ4ViT: Post-Training Quantization Framework for Vision Transformers.

Zhihang Yuan, Chenhao Xue, Yiqi Chen, Qiang Wu, Guangyu Sun

CoRR, 2021

PTQ-SL: Exploring the Sub-layerwise Post-training Quantization.

Zhihang Yuan, Yiqi Chen, Chenhao Xue, Chenguang Zhang, Qiankun Wang, Guangyu Sun

CoRR, 2021

METRO: A Software-Hardware Co-Design of Interconnections for Spatial DNN Accelerators.

Zhao Wang, Guangyu Sun, Jingchen Zhu, Zhe Zhou, Yijiang Guo, Zhihang Yuan

CoRR, 2021

NAS4RRAM: neural network architecture search for inference on RRAM-based accelerators.

Zhihang Yuan, Jingze Liu, Xingchen Li, Longhao Yan, Haoxiang Chen, Bingzhe Wu, Yuchao Yang, Guangyu Sun

Sci. China Inf. Sci., 2021

Rapid Configuration of Asynchronous Recurrent Neural Networks for ASIC Implementations.

Spencer Nelson, Wassim Khalil, SangYun Kim, Jia Di, Zhe Zhou, Zhihang Yuan, Guang-Yu Sun

Proceedings of the 2021 IEEE High Performance Extreme Computing Conference, 2021

Reconfigurable ASIC Implementation of Asynchronous Recurrent Neural Networks.

Spencer Nelson, Sang Yun Kim, Jia Di, Zhe Zhou, Zhihang Yuan, Guangyu Sun

Proceedings of the 27th IEEE International Symposium on Asynchronous Circuits and Systems, 2021

2020

Crane: Mitigating Accelerator Under-utilization Caused by Sparsity Irregularities in CNNs.

Yijin Guan, Guangyu Sun, Zhihang Yuan, Xingchen Li, Ningyi Xu, Shu Chen, Jason Cong, Yuan Xie

IEEE Trans. Computers, 2020

ENAS4D: Efficient Multi-stage CNN Architecture Search for Dynamic Inference.

Zhihang Yuan, Xin Liu, Bingzhe Wu, Guangyu Sun

CoRR, 2020

S2DNAS: Transforming Static CNN Model for Dynamic Inference via Neural Architecture Search.

Zhihang Yuan, Bingzhe Wu, Guangyu Sun, Zheng Liang, Shiwan Zhao, Weichen Bi

Proceedings of the Computer Vision - ECCV 2020, 2020

2017

Reducing Overfitting in Deep Convolutional Neural Networks Using Redundancy Regularizer.

Bingzhe Wu, Zhichao Liu, Zhihang Yuan, Guangyu Sun, Charles Wu

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2017, 2017

FPGA-based accelerator for long short-term memory recurrent neural networks.

Yijin Guan, Zhihang Yuan, Guangyu Sun, Jason Cong

Proceedings of the 22nd Asia and South Pacific Design Automation Conference, 2017

Using Data Compression for Optimizing FPGA-Based Convolutional Neural Network Accelerators.

Yijin Guan, Ningyi Xu, Chen Zhang, Zhihang Yuan, Jason Cong

Proceedings of the Advanced Parallel Processing Technologies, 2017