Zhihang Yuan

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 50

Top Topics

Diffusion Models

Mutual Information Maximization

Top Venues

ACM Trans. Embed. Comput. Syst.

Publications

Chenguang Zhang, Zhihang Yuan, Xingchen Li, Guangyu Sun
Algorithm-Hardware Co-Design for Energy-Efficient A/D Conversion in ReRAM-Based Accelerators. DATE (2024)
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
LLM Inference Unveiled: Survey and Roofline Model Insights. CoRR (2024)
Xing Hu, Yuan Cheng, Dawei Yang, Zhihang Yuan, Jiangyong Yu, Chen Xu, Sifan Zhou
I-LLM: Efficient Integer-Only Inference for Fully-Quantized Low-Bit Large Language Models. CoRR (2024)
Haoxuan Wang, Yuzhang Shang, Zhihang Yuan, Junyi Wu, Yan Yan
QuEST: Low-bit Diffusion Model Quantization via Efficient Selective Finetuning. CoRR (2024)
Chuanhao Sun, Zhihang Yuan, Kai Xu, Luo Mai, N. Siddharth, Shuo Chen, Mahesh K. Marina
Learning High-Frequency Functions Made Easy with Sinusoidal Positional Encoding. CoRR (2024)
Kai Wang, Yukun Zhou, Mingjia Shi, Zhihang Yuan, Yuzhang Shang, Xiaojiang Peng, Hanwang Zhang, Yang You
A Closer Look at Time Steps is Worthy of Triple Speed-Up for Diffusion Model Training. CoRR (2024)
Haojie Duanmu, Zhihang Yuan, Xiuhong Li, Jiangfei Duan, Xingcheng Zhang, Dahua Lin
SKVQ: Sliding-window Key and Value Cache Quantization for Large Language Models. CoRR (2024)
Zhihang Yuan, Pu Lu, Hanling Zhang, Xuefei Ning, Linfeng Zhang, Tianchen Zhao, Shengen Yan, Guohao Dai, Yu Wang
DiTFastAttn: Attention Compression for Diffusion Transformer Models. CoRR (2024)
Zhenyang Hao, Xinggang Wang, Jiawei Liu, Zhihang Yuan, Dawei Yang, Wenyu Liu
Stabilized activation scale estimation for precise Post-Training Quantization. Neurocomputing 569 (2024)
Sifan Zhou, Zhihang Yuan, Dawei Yang, Xubin Wen, Xing Hu, Yuguang Shi, Ziyu Zhao, Xiaobo Lu
PillarHist: A Quantization-aware Pillar Feature Encoder based on Height-aware Histogram. CoRR (2024)
Weisheng Xu, Sifan Zhou, Zhihang Yuan
PillarTrack: Redesigning Pillar-based Transformer Network for Single Object Tracking on Point Clouds. CoRR (2024)
Yuxuan Yue, Zhihang Yuan, Haojie Duanmu, Sifan Zhou, Jianlong Wu, Liqiang Nie
WKVQuant: Quantizing Weight and Key/Value Cache for Large Language Models Gains More. CoRR (2024)
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
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. ISSCC (2024)
Chenguang Zhang, Zhihang Yuan, Xingchen Li, Guangyu Sun
Algorithm-hardware co-design for Energy-Efficient A/D conversion in ReRAM-based accelerators. CoRR (2024)
Dawei Yang, Ning He, Xing Hu, Zhihang Yuan, Jiangyong Yu, Chen Xu, Zhe Jiang
Post-training quantization for re-parameterization via coarse & fine weight splitting. J. Syst. Archit. 147 (2024)
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
A Survey on Efficient Inference for Large Language Models. CoRR (2024)
Zhihang Yuan, Yuzhang Shang, Zhen Dong
PB-LLM: Partially Binarized Large Language Models. ICLR (2024)
Yuzhang Shang, Zhihang Yuan, Qiang Wu, Zhen Dong
PB-LLM: Partially Binarized Large Language Models. CoRR (2023)
Zhihang Yuan, Yuzhang Shang, Yue Song, Qiang Wu, Yan Yan, Guangyu Sun
ASVD: Activation-aware Singular Value Decomposition for Compressing Large Language Models. CoRR (2023)
Zhihang Yuan, Lin Niu, Jiawei Liu, Wenyu Liu, Xinggang Wang, Yuzhang Shang, Guangyu Sun, Qiang Wu, Jiaxiang Wu, Bingzhe Wu
RPTQ: Reorder-based Post-training Quantization for Large Language Models. CoRR (2023)
Zhihang Yuan, Jiawei Liu, Jiaxiang Wu, Dawei Yang, Qiang Wu, Guangyu Sun, Wenyu Liu, Xinggang Wang, Bingzhe Wu
Benchmarking the Reliability of Post-training Quantization: a Particular Focus on Worst-case Performance. CoRR (2023)
Yizeng Han, Zeyu Liu, Zhihang Yuan, Yifan Pu, Chaofei Wang, Shiji Song, Gao Huang
Latency-aware Unified Dynamic Networks for Efficient Image Recognition. CoRR (2023)
Yuzhang Shang, Zhihang Yuan, Bin Xie, Bingzhe Wu, Yan Yan
Post-Training Quantization on Diffusion Models. CVPR (2023)
Dawei Yang, Ning He, Xing Hu, Zhihang Yuan, Jiangyong Yu, Chen Xu, Zhe Jiang
Post-Training Quantization for Re-parameterization via Coarse & Fine Weight Splitting. CoRR (2023)
Jiawei Liu, Lin Niu, Zhihang Yuan, Dawei Yang, Xinggang Wang, Wenyu Liu
PD-Quant: Post-Training Quantization Based on Prediction Difference Metric. CVPR (2023)
Yuzhang Shang, Zhihang Yuan, Yan Yan
MIM4DD: Mutual Information Maximization for Dataset Distillation. NeurIPS (2023)
Lin Niu, Jiawei Liu, Zhihang Yuan, Dawei Yang, Xinggang Wang, Wenyu Liu
Post-Training Quantization for Object Detection. CoRR (2023)
Xiaoyang Wang, Zhe Zhou, Zhihang Yuan, Jingchen Zhu, Yulong Cao, Yao Zhang, Kangrui Sun, Guangyu Sun
FD-CNN: A Frequency-Domain FPGA Acceleration Scheme for CNN-Based Image-Processing Applications. ACM Trans. Embed. Comput. Syst. 22 (6) (2023)
Yuzhang Shang, Zhihang Yuan, Yan Yan
MIM4DD: Mutual Information Maximization for Dataset Distillation. CoRR (2023)
Xingchen Li, Zhihang Yuan, Yijin Guan, Guangyu Sun, Tao Zhang, Rongshan Wei, Dimin Niu
Flatfish: A Reinforcement Learning Approach for Application-Aware Address Mapping. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 41 (11) (2022)
Yuzhang Shang, Zhihang Yuan, Bin Xie, Bingzhe Wu, Yan Yan
Post-training Quantization on Diffusion Models. CoRR (2022)
Jiawei Liu, Lin Niu, Zhihang Yuan, Dawei Yang, Xinggang Wang, Wenyu Liu
PD-Quant: Post-Training Quantization based on Prediction Difference Metric. CoRR (2022)
Yizeng Han, Zhihang Yuan, Yifan Pu, Chenhao Xue, Shiji Song, Guangyu Sun, Gao Huang
Latency-aware Spatial-wise Dynamic Networks. CoRR (2022)
Xingchen Li, Zhihang Yuan, Guangyu Sun, Liang Zhao, Zhichao Lu
Tailor: removing redundant operations in memristive analog neural network accelerators. DAC (2022)
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
Enabling High-Quality Uncertainty Quantification in a PIM Designed for Bayesian Neural Network. HPCA (2022)
Yizeng Han, Zhihang Yuan, Yifan Pu, Chenhao Xue, Shiji Song, Guangyu Sun, Gao Huang
Latency-aware Spatial-wise Dynamic Networks. NeurIPS (2022)
Zhihang Yuan, Chenhao Xue, Yiqi Chen, Qiang Wu, Guangyu Sun
PTQ4ViT: Post-training Quantization for Vision Transformers with Twin Uniform Quantization. ECCV (12) (2022)
Zhihang Yuan, Chenhao Xue, Yiqi Chen, Qiang Wu, Guangyu Sun
PTQ4ViT: Post-Training Quantization Framework for Vision Transformers. CoRR (2021)
Spencer Nelson, Sang Yun Kim, Jia Di, Zhe Zhou, Zhihang Yuan, Guangyu Sun
Reconfigurable ASIC Implementation of Asynchronous Recurrent Neural Networks. ASYNC (2021)
Zhihang Yuan, Jingze Liu, Xingchen Li, Longhao Yan, Haoxiang Chen, Bingzhe Wu, Yuchao Yang, Guangyu Sun
NAS4RRAM: neural network architecture search for inference on RRAM-based accelerators. Sci. China Inf. Sci. 64 (6) (2021)
Spencer Nelson, Wassim Khalil, Sang Yun Kim, Jia Di, Zhe Zhou, Zhihang Yuan, Guang-Yu Sun
Rapid Configuration of Asynchronous Recurrent Neural Networks for ASIC Implementations. HPEC (2021)
Zhihang Yuan, Yiqi Chen, Chenhao Xue, Chenguang Zhang, Qiankun Wang, Guangyu Sun
PTQ-SL: Exploring the Sub-layerwise Post-training Quantization. CoRR (2021)
Zhao Wang, Guangyu Sun, Jingchen Zhu, Zhe Zhou, Yijiang Guo, Zhihang Yuan
METRO: A Software-Hardware Co-Design of Interconnections for Spatial DNN Accelerators. CoRR (2021)
Zhihang Yuan, Bingzhe Wu, Guangyu Sun, Zheng Liang, Shiwan Zhao, Weichen Bi
S2DNAS: Transforming Static CNN Model for Dynamic Inference via Neural Architecture Search. ECCV (2) (2020)
Yijin Guan, Guangyu Sun, Zhihang Yuan, Xingchen Li, Ningyi Xu, Shu Chen, Jason Cong, Yuan Xie
Crane: Mitigating Accelerator Under-utilization Caused by Sparsity Irregularities in CNNs. IEEE Trans. Computers 69 (7) (2020)
Zhihang Yuan, Xin Liu, Bingzhe Wu, Guangyu Sun
ENAS4D: Efficient Multi-stage CNN Architecture Search for Dynamic Inference. CoRR (2020)
Zhihang Yuan, Bingzhe Wu, Zheng Liang, Shiwan Zhao, Weichen Bi, Guangyu Sun
S2DNAS: Transforming Static CNN Model for Dynamic Inference via Neural Architecture Search. CoRR (2019)
Yijin Guan, Zhihang Yuan, Guangyu Sun, Jason Cong
FPGA-based accelerator for long short-term memory recurrent neural networks. ASP-DAC (2017)
Bingzhe Wu, Zhichao Liu, Zhihang Yuan, Guangyu Sun, Charles Wu
Reducing Overfitting in Deep Convolutional Neural Networks Using Redundancy Regularizer. ICANN (2) (2017)
Yijin Guan, Ningyi Xu, Chen Zhang, Zhihang Yuan, Jason Cong
Using Data Compression for Optimizing FPGA-Based Convolutional Neural Network Accelerators. APPT (2017)