Zhihang Yuan - RankMe

101 papers A* 22A 1B 1Journal 66Unranked 11

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	6Bit-Diffusion: Inference-Time Mixed-Precision Quantization for Video Diffusion Models. CoRR Rundong Su, Jintao Zhang, Zhihang Yuan, Haojie Duanmu, Jianfei Chen, Jun Zhu
2026	J	`jnl`	AltTS: A Dual-Path Framework with Alternating Optimization for Multivariate Time Series Forecasting. CoRR Zhihang Yuan, Zhiyuan Liu, Mahesh K. Marina
2026	A*	`conf`	OTARo: Once Tuning for All Precisions Toward Robust On-Device LLMs. AAAI Shaoyuan Chen, Zhixuan Chen, Dawei Yang, Zhihang Yuan, Qiang Wu
2026	J	`jnl`	TUBO: A Tailored ML Framework for Reliable Network Traffic Forecasting. CoRR Zhihang Yuan, Leyang Xue, Waleed Ahsan, Mahesh K. Marina
2026	J	`jnl`	Uncertainty-Aware Gradient Signal-to-Noise Data Selection for Instruction Tuning. CoRR Zhihang Yuan, Chengyu Yue, Long Huang, Litu Ou, Lei Shi
2025	J	`jnl`	A 22-nm 64-kB lightning-like hybrid computing-in-memory macro with a compressed adder tree and analog-storage quantizers for transformer and CNNs. Sci. China Inf. Sci. An Guo, Xi Chen, Fangyuan Dong, Jinwu Chen, Zhihang Yuan, Xing Hu, Guangyu Sun, Xiaomin Li, Arindam Basu, Jun Yang, Xin Si
2025	A*	`conf`	A Closer Look at Time Steps is Worthy of Triple Speed-Up for Diffusion Model Training. CVPR Kai Wang, Mingjia Shi, Yukun Zhou, Zekai Li, Zhihang Yuan, Yuzhang Shang, Xiaojiang Peng, Hanwang Zhang, Yang You
2025	A*	`conf`	AIM: Software and Hardware Co-design for Architecture-level IR-drop Mitigation in High-performance PIM. ISCA Yuanpeng Zhang, Xing Hu, Xi Chen, Zhihang Yuan, Cong Li, Jingchen Zhu, Zhao Wang, Chenguang Zhang, Xin Si, Wei Gao, Qiang Wu, Runsheng Wang, Guangyu Sun
2025	J	`jnl`	AIM: Software and Hardware Co-design for Architecture-level IR-drop Mitigation in High-performance PIM. CoRR Yuanpeng Zhang, Xing Hu, Xi Chen, Zhihang Yuan, Cong Li, Jingchen Zhu, Zhao Wang, Chenguang Zhang, Xin Si, Wei Gao, Qiang Wu, Runsheng Wang, Guangyu Sun
2025	B	`conf`	Bidirectional Multitask Learning for Non-Autoregressive Machine Translation. IJCNN Songsheng Wang, Shijie Zhang, Zhihang Yuan, Dongkun Wang, Derek F. Wong
2025	A*	`conf`	DLFR-VAE: Dynamic Latent Frame Rate VAE for Video Generation. ACM Multimedia Zhihang Yuan, Siyuan Wang, Yuzhang Shang, Hanling Zhang, Tongcheng Fang, Rui Xie, Shengen Yan, Guohao Dai, Yu Wang
2025	J	`jnl`	DLFR-VAE: Dynamic Latent Frame Rate VAE for Video Generation. CoRR Zhihang Yuan, Siyuan Wang, Rui Xie, Hanling Zhang, Tongcheng Fang, Yuzhang Shang, Shengen Yan, Guohao Dai, Yu Wang
2025	J	`jnl`	DiTFastAttnV2: Head-wise Attention Compression for Multi-Modality Diffusion Transformers. CoRR Hanling Zhang, Rundong Su, Zhihang Yuan, Pengtao Chen, Mingzhu Shen, Yibo Fan, Shengen Yan, Guohao Dai, Yu Wang
2025	J	`jnl`	EA-ViT: Efficient Adaptation for Elastic Vision Transformer. CoRR Chen Zhu, Wangbo Zhao, Huiwen Zhang, Samir Khaki, Yuhao Zhou, Weidong Tang, Shuo Wang, Zhihang Yuan, Yuzhang Shang, Xiaojiang Peng, Kai Wang, Dawei Yang
2025	—	`conf`	GSQ-Tuning: Group-Shared Exponents Integer in Fully Quantized Training for LLMs On-Device Fine-tuning. ACL (Findings) Sifan Zhou, Shuo Wang, Zhihang Yuan, Mingjia Shi, Yuzhang Shang, Dawei Yang
2025	J	`jnl`	GSQ-Tuning: Group-Shared Exponents Integer in Fully Quantized Training for LLMs On-Device Fine-tuning. CoRR Sifan Zhou, Shuo Wang, Zhihang Yuan, Mingjia Shi, Yuzhang Shang, Dawei Yang
2025	J	`jnl`	INT v.s. FP: A Comprehensive Study of Fine-Grained Low-bit Quantization Formats. CoRR Mengzhao Chen, Meng Wu, Hui Jin, Zhihang Yuan, Jing Liu, Chaoyi Zhang, Yunshui Li, Jie Huang, Jin Ma, Zeyue Xue, Zhiheng Liu, Xingyan Bin, Ping Luo
2025	J	`jnl`	Know When to Explore: Difficulty-Aware Certainty as a Guide for LLM Reinforcement Learning. CoRR Ang Li, Zhihang Yuan, Yang Zhang, Shouda Liu, Yisen Wang
2025	J	`jnl`	LANPO: Bootstrapping Language and Numerical Feedback for Reinforcement Learning in LLMs. CoRR Ang Li, Yifei Wang, Zhihang Yuan, Stefanie Jegelka, Yisen Wang
2025	J	`jnl`	MQuant: Unleashing the Inference Potential of Multimodal Large Language Models via Full Static Quantization. CoRR Jiangyong Yu, Sifan Zhou, Dawei Yang, Shuo Wang, Shuoyu Li, Xing Hu, Chen Xu, Zukang Xu, Changyong Shu, Zhihang Yuan
2025	A*	`conf`	MQuant: Unleashing the Inference Potential of Multimodal Large Language Models via Static Quantization. ACM Multimedia Jiangyong Yu, Sifan Zhou, Dawei Yang, Shuoyu Li, Shuo Wang, Xing Hu, Chen Xu, Zukang Xu, Changyong Shu, Zhihang Yuan
2025	A*	`conf`	MVCTrack: Boosting 3D Point Cloud Tracking via Multimodal-Guided Virtual Cues. ICRA Zhaofeng Hu, Sifan Zhou, Zhihang Yuan, Dawei Yang, Shibo Zhao, Ci-Jyun Liang
2025	A*	`conf`	MambaQuant: Quantizing the Mamba Family with Variance Aligned Rotation Methods. ICLR Zukang Xu, Yuxuan Yue, Xing Hu, Dawei Yang, Zhihang Yuan, Zixu Jiang, Zhixuan Chen, Jiangyong Yu, Chen Xu, Sifan Zhou
2025	J	`jnl`	MambaQuant: Quantizing the Mamba Family with Variance Aligned Rotation Methods. CoRR Zukang Xu, Yuxuan Yue, Xing Hu, Zhihang Yuan, Zixu Jiang, Zhixuan Chen, Jiangyong Yu, Chen Xu, Sifan Zhou, Dawei Yang
2025	J	`jnl`	MoDES: Accelerating Mixture-of-Experts Multimodal Large Language Models via Dynamic Expert Skipping. CoRR Yushi Huang, Zining Wang, Zhihang Yuan, Yifu Ding, Ruihao Gong, Jinyang Guo, Xianglong Liu, Jun Zhang
2025	A*	`conf`	MoEQuant: Enhancing Quantization for Mixture-of-Experts Large Language Models via Expert-Balanced Sampling and Affinity Guidance. ICML Zhixuan Chen, Xing Hu, Dawei Yang, Zukang Xu, Chen Xu, Zhihang Yuan, Sifan Zhou, Jiangyong Yu
2025	J	`jnl`	MoEQuant: Enhancing Quantization for Mixture-of-Experts Large Language Models via Expert-Balanced Sampling and Affinity Guidance. CoRR Xing Hu, Zhixuan Chen, Dawei Yang, Zukang Xu, Chen Xu, Zhihang Yuan, Sifan Zhou, Jiangyong Yu
2025	A*	`conf`	MxMoE: Mixed-precision Quantization for MoE with Accuracy and Performance Co-Design. ICML Haojie Duanmu, Xiuhong Li, Zhihang Yuan, Size Zheng, Jiangfei Duan, Xingcheng Zhang, Dahua Lin
2025	J	`jnl`	MxMoE: Mixed-precision Quantization for MoE with Accuracy and Performance Co-Design. CoRR Haojie Duanmu, Xiuhong Li, Zhihang Yuan, Size Zheng, Jiangfei Duan, Xingcheng Zhang, Dahua Lin
2025	A*	`conf`	OSTQuant: Refining Large Language Model Quantization with Orthogonal and Scaling Transformations for Better Distribution Fitting. ICLR Xing Hu, Yuan Cheng, Dawei Yang, Zhixuan Chen, Zukang Xu, Jiangyong Yu, Chen Xu, Zhihang Yuan, Zhe Jiang, Sifan Zhou
2025	J	`jnl`	OTARo: Once Tuning for All Precisions toward Robust On-Device LLMs. CoRR Shaoyuan Chen, Zhixuan Chen, Dawei Yang, Zhihang Yuan, Qiang Wu
2025	J	`jnl`	OstQuant: Refining Large Language Model Quantization with Orthogonal and Scaling Transformations for Better Distribution Fitting. CoRR Xing Hu, Yuan Cheng, Dawei Yang, Zukang Xu, Zhihang Yuan, Jiangyong Yu, Chen Xu, Zhe Jiang, Sifan Zhou
2025	J	`jnl`	PCDVQ: Enhancing Vector Quantization for Large Language Models via Polar Coordinate Decoupling. CoRR Yuxuan Yue, Zukang Xu, Zhihang Yuan, Dawei Yang, Jianlong Wu, Liqiang Nie
2025	A*	`conf`	PillarHist: A Quantization-aware Pillar Feature Encoder based on Height-aware Histogram. CVPR Sifan Zhou, Zhihang Yuan, Dawei Yang, Xing Hu, Jian Qian, Ziyu Zhao
2025	J	`jnl`	R2R: Efficiently Navigating Divergent Reasoning Paths with Small-Large Model Token Routing. CoRR Tianyu Fu, Yi Ge, Yichen You, Enshu Liu, Zhihang Yuan, Guohao Dai, Shengen Yan, Huazhong Yang, Yu Wang
2025	A*	`conf`	RWKVQuant: Quantizing the RWKV Family with Proxy Guided Hybrid of Scalar and Vector Quantization. ICML Chen Xu, Yuxuan Yue, Zukang Xu, Xing Hu, Jiangyong Yu, Zhixuan Chen, Sifan Zhou, Zhihang Yuan, Dawei Yang
2025	J	`jnl`	RWKVQuant: Quantizing the RWKV Family with Proxy Guided Hybrid of Scalar and Vector Quantization. CoRR Chen Xu, Yuxuan Yue, Zukang Xu, Xing Hu, Jiangyong Yu, Zhixuan Chen, Sifan Zhou, Zhihang Yuan, Dawei Yang
2025	J	`jnl`	SAFEx: Analyzing Vulnerabilities of MoE-Based LLMs via Stable Safety-critical Expert Identification. CoRR ZhengLin Lai, MengYao Liao, Dong Xu, Zebin Zhao, Zhihang Yuan, Chao Fan, Jianqiang Li, Bingzhe Wu
2025	A*	`conf`	Spec-VLA: Speculative Decoding for Vision-Language-Action Models with Relaxed Acceptance. EMNLP Songsheng Wang, Rucheng Yu, Zhihang Yuan, Chao Yu, Feng Gao, Yu Wang, Derek F. Wong
2025	J	`jnl`	Spec-VLA: Speculative Decoding for Vision-Language-Action Models with Relaxed Acceptance. CoRR Songsheng Wang, Rucheng Yu, Zhihang Yuan, Chao Yu, Feng Gao, Yu Wang, Derek F. Wong
2025	J	`jnl`	SplitMeanFlow: Interval Splitting Consistency in Few-Step Generative Modeling. CoRR Yi Guo, Wei Wang, Zhihang Yuan, Rong Cao, Kuan Chen, Zhengyang Chen, Yuanyuan Huo, Yang Zhang, Yuping Wang, Shouda Liu, Yuxuan Wang
2025	J	`jnl`	VGDFR: Diffusion-based Video Generation with Dynamic Latent Frame Rate. CoRR Zhihang Yuan, Rui Xie, Yuzhang Shang, Hanling Zhang, Siyuan Wang, Shengen Yan, Guohao Dai, Yu Wang
2025	J	`jnl`	VocabTailor: Dynamic Vocabulary Selection for Downstream Tasks in Small Language Models. CoRR Hanling Zhang, Yayu Zhou, Tongcheng Fang, Zhihang Yuan, Guohao Dai, Yu Wang
2024	—	`conf`	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 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
2024	J	`jnl`	A Closer Look at Time Steps is Worthy of Triple Speed-Up for Diffusion Model Training. CoRR Kai Wang, Yukun Zhou, Mingjia Shi, Zhihang Yuan, Yuzhang Shang, Xiaojiang Peng, Hanwang Zhang, Yang You
2024	—	`conf`	A Force Control Method of Medical Robot Based on Impedance Control. ROBIO Zhihang Yuan, Linshuai Zhang, Tao Jiang, Shuoxin Gu, Lin Xu, Yujie Zhang, Peng Zeng, Marcin Grzegorzek
2024	J	`jnl`	A Survey on Efficient Inference for Large Language Models. CoRR 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
2024	A	`conf`	Algorithm-Hardware Co-Design for Energy-Efficient A/D Conversion in ReRAM-Based Accelerators. DATE Chenguang Zhang, Zhihang Yuan, Xingchen Li, Guangyu Sun
2024	J	`jnl`	Algorithm-hardware co-design for Energy-Efficient A/D conversion in ReRAM-based accelerators. CoRR Chenguang Zhang, Zhihang Yuan, Xingchen Li, Guangyu Sun
2024	—	`conf`	CSKV: Training-Efficient Channel Shrinking for KV Cache in Long-Context Scenarios. ENLSP Luning Wang, Shiyao Li, Xuefei Ning, Zhihang Yuan, Shengen Yan, Guohao Dai, Yu Wang
2024	J	`jnl`	CSKV: Training-Efficient Channel Shrinking for KV Cache in Long-Context Scenarios. CoRR Luning Wang, Shiyao Li, Xuefei Ning, Zhihang Yuan, Shengen Yan, Guohao Dai, Yu Wang
2024	A*	`conf`	DiTFastAttn: Attention Compression for Diffusion Transformer Models. NeurIPS Zhihang Yuan, Hanling Zhang, Lu Pu, Xuefei Ning, Linfeng Zhang, Tianchen Zhao, Shengen Yan, Guohao Dai, Yu Wang
2024	J	`jnl`	DiTFastAttn: Attention Compression for Diffusion Transformer Models. CoRR Zhihang Yuan, Pu Lu, Hanling Zhang, Xuefei Ning, Linfeng Zhang, Tianchen Zhao, Shengen Yan, Guohao Dai, Yu Wang
2024	J	`jnl`	E-CAR: Efficient Continuous Autoregressive Image Generation via Multistage Modeling. CoRR Zhihang Yuan, Yuzhang Shang, Hanling Zhang, Tongcheng Fang, Rui Xie, Bingxin Xu, Yan Yan, Shengen Yan, Guohao Dai, Yu Wang
2024	J	`jnl`	I-LLM: Efficient Integer-Only Inference for Fully-Quantized Low-Bit Large Language Models. CoRR Xing Hu, Yuan Cheng, Dawei Yang, Zhihang Yuan, Jiangyong Yu, Chen Xu, Sifan Zhou
2024	J	`jnl`	LLM Inference Unveiled: Survey and Roofline Model Insights. CoRR 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
2024	J	`jnl`	Latency-Aware Unified Dynamic Networks for Efficient Image Recognition. IEEE Trans. Pattern Anal. Mach. Intell. Yizeng Han, Zeyu Liu, Zhihang Yuan, Yifan Pu, Chaofei Wang, Shiji Song, Gao Huang
2024	A*	`conf`	Learning High-Frequency Functions Made Easy with Sinusoidal Positional Encoding. ICML Chuanhao Sun, Zhihang Yuan, Kai Xu, Luo Mai, N. Siddharth, Shuo Chen, Mahesh K. Marina
2024	J	`jnl`	Learning High-Frequency Functions Made Easy with Sinusoidal Positional Encoding. CoRR Chuanhao Sun, Zhihang Yuan, Kai Xu, Luo Mai, N. Siddharth, Shuo Chen, Mahesh K. Marina
2024	J	`jnl`	LiteVAR: Compressing Visual Autoregressive Modelling with Efficient Attention and Quantization. CoRR Rui Xie, Tianchen Zhao, Zhihang Yuan, Rui Wan, Wenxi Gao, Zhenhua Zhu, Xuefei Ning, Yu Wang
2024	J	`jnl`	MVCTrack: Boosting 3D Point Cloud Tracking via Multimodal-Guided Virtual Cues. CoRR Zhaofeng Hu, Sifan Zhou, Shibo Zhao, Zhihang Yuan
2024	A*	`conf`	PB-LLM: Partially Binarized Large Language Models. ICLR Zhihang Yuan, Yuzhang Shang, Zhen Dong
2024	J	`jnl`	PillarTrack: Redesigning Pillar-based Transformer Network for Single Object Tracking on Point Clouds. CoRR Weisheng Xu, Sifan Zhou, Zhihang Yuan
2024	J	`jnl`	Post-training quantization for re-parameterization via coarse & fine weight splitting. J. Syst. Archit. Dawei Yang, Ning He, Xing Hu, Zhihang Yuan, Jiangyong Yu, Chen Xu, Zhe Jiang
2024	J	`jnl`	QuEST: Low-bit Diffusion Model Quantization via Efficient Selective Finetuning. CoRR Haoxuan Wang, Yuzhang Shang, Zhihang Yuan, Junyi Wu, Yan Yan
2024	J	`jnl`	SKVQ: Sliding-window Key and Value Cache Quantization for Large Language Models. CoRR Haojie Duanmu, Zhihang Yuan, Xiuhong Li, Jiangfei Duan, Xingcheng Zhang, Dahua Lin
2024	J	`jnl`	Stabilized activation scale estimation for precise Post-Training Quantization. Neurocomputing Zhenyang Hao, Xinggang Wang, Jiawei Liu, Zhihang Yuan, Dawei Yang, Wenyu Liu
2024	J	`jnl`	WKVQuant: Quantizing Weight and Key/Value Cache for Large Language Models Gains More. CoRR Yuxuan Yue, Zhihang Yuan, Haojie Duanmu, Sifan Zhou, Jianlong Wu, Liqiang Nie
2023	J	`jnl`	ASVD: Activation-aware Singular Value Decomposition for Compressing Large Language Models. CoRR Zhihang Yuan, Yuzhang Shang, Yue Song, Qiang Wu, Yan Yan, Guangyu Sun
2023	J	`jnl`	Benchmarking the Reliability of Post-training Quantization: a Particular Focus on Worst-case Performance. CoRR Zhihang Yuan, Jiawei Liu, Jiaxiang Wu, Dawei Yang, Qiang Wu, Guangyu Sun, Wenyu Liu, Xinggang Wang, Bingzhe Wu
2023	J	`jnl`	FD-CNN: A Frequency-Domain FPGA Acceleration Scheme for CNN-Based Image-Processing Applications. ACM Trans. Embed. Comput. Syst. Xiaoyang Wang, Zhe Zhou, Zhihang Yuan, Jingchen Zhu, Yulong Cao, Yao Zhang, Kangrui Sun, Guangyu Sun
2023	J	`jnl`	Improving Post-Training Quantization on Object Detection with Task Loss-Guided Lp Metric. CoRR Lin Niu, Jiawei Liu, Zhihang Yuan, Dawei Yang, Xinggang Wang, Wenyu Liu
2023	J	`jnl`	Latency-aware Unified Dynamic Networks for Efficient Image Recognition. CoRR Yizeng Han, Zeyu Liu, Zhihang Yuan, Yifan Pu, Chaofei Wang, Shiji Song, Gao Huang
2023	A*	`conf`	MIM4DD: Mutual Information Maximization for Dataset Distillation. NeurIPS Yuzhang Shang, Zhihang Yuan, Yan Yan
2023	J	`jnl`	MIM4DD: Mutual Information Maximization for Dataset Distillation. CoRR Yuzhang Shang, Zhihang Yuan, Yan Yan
2023	J	`jnl`	PB-LLM: Partially Binarized Large Language Models. CoRR Yuzhang Shang, Zhihang Yuan, Qiang Wu, Zhen Dong
2023	A*	`conf`	PD-Quant: Post-Training Quantization Based on Prediction Difference Metric. CVPR Jiawei Liu, Lin Niu, Zhihang Yuan, Dawei Yang, Xinggang Wang, Wenyu Liu
2023	J	`jnl`	Post-Training Quantization for Re-parameterization via Coarse & Fine Weight Splitting. CoRR Dawei Yang, Ning He, Xing Hu, Zhihang Yuan, Jiangyong Yu, Chen Xu, Zhe Jiang
2023	A*	`conf`	Post-Training Quantization on Diffusion Models. CVPR Yuzhang Shang, Zhihang Yuan, Bin Xie, Bingzhe Wu, Yan Yan
2023	J	`jnl`	RPTQ: Reorder-based Post-training Quantization for Large Language Models. CoRR Zhihang Yuan, Lin Niu, Jiawei Liu, Wenyu Liu, Xinggang Wang, Yuzhang Shang, Guangyu Sun, Qiang Wu, Jiaxiang Wu, Bingzhe Wu
2022	A*	`conf`	Enabling High-Quality Uncertainty Quantification in a PIM Designed for Bayesian Neural Network. HPCA 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
2022	J	`jnl`	Flatfish: A Reinforcement Learning Approach for Application-Aware Address Mapping. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. Xingchen Li, Zhihang Yuan, Yijin Guan, Guangyu Sun, Tao Zhang, Rongshan Wei, Dimin Niu
2022	A*	`conf`	Latency-aware Spatial-wise Dynamic Networks. NeurIPS Yizeng Han, Zhihang Yuan, Yifan Pu, Chenhao Xue, Shiji Song, Guangyu Sun, Gao Huang
2022	J	`jnl`	Latency-aware Spatial-wise Dynamic Networks. CoRR Yizeng Han, Zhihang Yuan, Yifan Pu, Chenhao Xue, Shiji Song, Guangyu Sun, Gao Huang
2022	J	`jnl`	PD-Quant: Post-Training Quantization based on Prediction Difference Metric. CoRR Jiawei Liu, Lin Niu, Zhihang Yuan, Dawei Yang, Xinggang Wang, Wenyu Liu
2022	—	`conf`	PTQ4ViT: Post-training Quantization for Vision Transformers with Twin Uniform Quantization. ECCV (12) Zhihang Yuan, Chenhao Xue, Yiqi Chen, Qiang Wu, Guangyu Sun
2022	J	`jnl`	Post-training Quantization on Diffusion Models. CoRR Yuzhang Shang, Zhihang Yuan, Bin Xie, Bingzhe Wu, Yan Yan
2022	A*	`conf`	Tailor: removing redundant operations in memristive analog neural network accelerators. DAC Xingchen Li, Zhihang Yuan, Guangyu Sun, Liang Zhao, Zhichao Lu
2021	J	`jnl`	METRO: A Software-Hardware Co-Design of Interconnections for Spatial DNN Accelerators. CoRR Zhao Wang, Guangyu Sun, Jingchen Zhu, Zhe Zhou, Yijiang Guo, Zhihang Yuan
2021	J	`jnl`	NAS4RRAM: neural network architecture search for inference on RRAM-based accelerators. Sci. China Inf. Sci. Zhihang Yuan, Jingze Liu, Xingchen Li, Longhao Yan, Haoxiang Chen, Bingzhe Wu, Yuchao Yang, Guangyu Sun
2021	J	`jnl`	PTQ-SL: Exploring the Sub-layerwise Post-training Quantization. CoRR Zhihang Yuan, Yiqi Chen, Chenhao Xue, Chenguang Zhang, Qiankun Wang, Guangyu Sun
2021	J	`jnl`	PTQ4ViT: Post-Training Quantization Framework for Vision Transformers. CoRR Zhihang Yuan, Chenhao Xue, Yiqi Chen, Qiang Wu, Guangyu Sun
2021	—	`conf`	Rapid Configuration of Asynchronous Recurrent Neural Networks for ASIC Implementations. HPEC Spencer Nelson, Wassim Khalil, SangYun Kim, Jia Di, Zhe Zhou, Zhihang Yuan, Guang-Yu Sun
2021	—	`conf`	Reconfigurable ASIC Implementation of Asynchronous Recurrent Neural Networks. ASYNC Spencer Nelson, Sang Yun Kim, Jia Di, Zhe Zhou, Zhihang Yuan, Guangyu Sun
2020	J	`jnl`	Crane: Mitigating Accelerator Under-utilization Caused by Sparsity Irregularities in CNNs. IEEE Trans. Computers Yijin Guan, Guangyu Sun, Zhihang Yuan, Xingchen Li, Ningyi Xu, Shu Chen, Jason Cong, Yuan Xie
2020	J	`jnl`	ENAS4D: Efficient Multi-stage CNN Architecture Search for Dynamic Inference. CoRR Zhihang Yuan, Xin Liu, Bingzhe Wu, Guangyu Sun
2020	—	`conf`	S2DNAS: Transforming Static CNN Model for Dynamic Inference via Neural Architecture Search. ECCV (2) Zhihang Yuan, Bingzhe Wu, Guangyu Sun, Zheng Liang, Shiwan Zhao, Weichen Bi
2019	J	`jnl`	S2DNAS: Transforming Static CNN Model for Dynamic Inference via Neural Architecture Search. CoRR Zhihang Yuan, Bingzhe Wu, Zheng Liang, Shiwan Zhao, Weichen Bi, Guangyu Sun
2017	—	`conf`	FPGA-based accelerator for long short-term memory recurrent neural networks. ASP-DAC Yijin Guan, Zhihang Yuan, Guangyu Sun, Jason Cong
2017	—	`conf`	Reducing Overfitting in Deep Convolutional Neural Networks Using Redundancy Regularizer. ICANN (2) Bingzhe Wu, Zhichao Liu, Zhihang Yuan, Guangyu Sun, Charles Wu
2017	—	`conf`	Using Data Compression for Optimizing FPGA-Based Convolutional Neural Network Accelerators. APPT Yijin Guan, Ningyi Xu, Chen Zhang, Zhihang Yuan, Jason Cong