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ORCIDShaoyi Huang
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- Shao-yin Huang
- Shaoyin Huang
- Shaoying Huang (aka: Shao Ying Huang)
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2020 – today
- 2026
[c25]Daniel Stein, Shaoyi Huang, Rolf Drechsler, Bing Li, Grace Li Zhang:
Late Breaking Results: Conversion of Neural Networks into Logic Flows for Edge Computing. DATE 2026: 1-3- [c24]Chence Yang
, Ningxi Cheng, Ci Zhang, Lei Lu, Qitao Tan, Sheng Li, Ao Li, Xulong Tang, Shaoyi Huang, Jinzhen Wang, Guoming Li, Jundong Li, Xiaoming Zhai, Jin Lu, Jinhui Wang, Geng Yuan:
Rethinking the Potential of Layer Freezing for DNN Training Efficiency. ACM Great Lakes Symposium on VLSI 2026: 772-778 - [i32]Daniel Stein, Shaoyi Huang, Rolf Drechsler, Bing Li, Grace Li Zhang:
Late Breaking Results: Conversion of Neural Networks into Logic Flows for Edge Computing. CoRR abs/2601.22151 (2026) - [i31]Zhendong Mi, Yixiao Chen, Pu Zhao, Xiaodong Yu, Hao Wang, Yanzhi Wang, Shaoyi Huang:
Effective MoE-based LLM Compression by Exploiting Heterogeneous Inter-Group Experts Routing Frequency and Information Density. CoRR abs/2602.09316 (2026) - [i30]Ci Zhang, Zhaojun Ding, Chence Yang, Jun Liu, Xiaoming Zhai, Shaoyi Huang, Beiwen Li, Xiaolong Ma, Jin Lu, Geng Yuan:
Roots Beneath the Cut: Uncovering the Risk of Concept Revival in Pruning-Based Unlearning for Diffusion Models. CoRR abs/2603.06640 (2026) - [i29]Yuebo Luo, Shiyang Li, Yifei Feng, Vishal Kancharla, Shaoyi Huang, Caiwen Ding:
GSR-GNN: Training Acceleration and Memory-Saving Framework of Deep GNNs on Circuit Graph. CoRR abs/2603.27156 (2026) - [i28]Dev Arpan Desai, Shaoyi Huang, Zining Zhu:
Distributed Interpretability and Control for Large Language Models. CoRR abs/2604.06483 (2026) - [i27]Hengyi Zhu, Zhendong Mi, Grace Li Zhang, Shaoyi Huang:
Different Prompts, Different Ranks: Prompt-aware Dynamic Rank Selection for SVD-based LLM Compression. CoRR abs/2605.08568 (2026) - 2025
- [c23]Kaleel Mahmood, Shaoyi Huang:
Efficient Context Propagating Perceiver Architectures for Auto-Regressive Language Modeling. ECAI 2025: 4428-4435 - [c22]Kiran Thorat, Hongwu Peng, Yuebo Luo, Xi Xie, Shaoyi Huang, Amit Hasan, Jiahui Zhao, Yingjie Li, Zhijie Shi, Cunxi Yu, Caiwen Ding:
GROOT: Graph Edge Re-growth and Partitioning for the Verification of Large Designs in Logic Synthesis. ICCAD 2025: 1-9 - [c21]Yuebo Luo, Shiyang Li, Junran Tao, Kiran Gautam Thorat, Xi Xie, Hongwu Peng, Nuo Xu, Caiwen Ding, Shaoyi Huang:
DR-CircuitGNN: Training Acceleration of Heterogeneous Circuit Graph Neural Network on GPUs. ICS 2025: 221-235 - [i26]Zhendong Mi, Qitao Tan, Xiaodong Yu, Zining Zhu, Geng Yuan, Shaoyi Huang:
KerZOO: Kernel Function Informed Zeroth-Order Optimization for Accurate and Accelerated LLM Fine-Tuning. CoRR abs/2505.18886 (2025) - [i25]Zhendong Mi, Zhenglun Kong, Geng Yuan, Shaoyi Huang:
ACE: Exploring Activation Cosine Similarity and Variance for Accurate and Calibration-Efficient LLM Pruning. CoRR abs/2505.21987 (2025) - [i24]Chence Yang, Ci Zhang, Le Lu, Qitao Tan, Sheng Li, Ao Li, Xulong Tang, Shaoyi Huang, Jinzhen Wang, Guoming Li, Jundong Li, Xiaoming Zhai, Jin Lu, Geng Yuan:
Rethinking the Potential of Layer Freezing for Efficient DNN Training. CoRR abs/2508.15033 (2025) - [i23]Yuebo Luo, Shiyang Li, Junran Tao, Kiran Thorat, Xi Xie, Hongwu Peng, Nuo Xu, Caiwen Ding, Shaoyi Huang:
DR-CircuitGNN: Training Acceleration of Heterogeneous Circuit Graph Neural Network on GPUs. CoRR abs/2508.16769 (2025) - [i22]Qitao Tan, Xiaoying Song, Jin Lu, Guoming Li, Jun Liu, Lingzi Hong, Caiwen Ding, Jundong Li, Xiaoming Zhai, Shaoyi Huang, Wei Niu, Geng Yuan:
End-to-End On-Device Quantization-Aware Training for LLMs at Inference Cost. CoRR abs/2509.00031 (2025) - [i21]Zhendong Mi, Bian Sun, Grace Li Zhang, Shaoyi Huang:
Layer-wise dynamic rank for compressing large language models. CoRR abs/2509.25622 (2025) - [i20]Hengyi Zhu, Grace Li Zhang, Shaoyi Huang:
PEL-NAS: Search Space Partitioned Architecture Prompt Co-Evolutionary LLM-driven Hardware-Aware Neural Architecture Search. CoRR abs/2510.01472 (2025) - [i19]Zhendong Mi, Qitao Tan, Grace Li Zhang, Zhaozhuo Xu, Geng Yuan, Shaoyi Huang:
Towards Fast LLM Fine-tuning through Zeroth-Order Optimization with Projected Gradient-Aligned Perturbations. CoRR abs/2510.18228 (2025) - [i18]Jiaxun Fang, Grace Li Zhang, Shaoyi Huang:
Layer-wise Weight Selection for Power-Efficient Neural Network Acceleration. CoRR abs/2511.17123 (2025) - [i17]Kiran Thorat, Hongwu Peng, Yuebo Luo, Xi Xie, Shaoyi Huang, Amit Hasan, Jiahui Zhao, Yingjie Li, Zhijie Shi, Cunxi Yu, Caiwen Ding:
GROOT: Graph Edge Re-growth and Partitioning for the Verification of Large Designs in Logic Synthesis. CoRR abs/2511.18297 (2025) - 2024
- [c20]Hongwu Peng, Xi Xie, Kaustubh Shivdikar, Md Amit Hasan, Jiahui Zhao, Shaoyi Huang, Omer Khan, David R. Kaeli, Caiwen Ding:
MaxK-GNN: Extremely Fast GPU Kernel Design for Accelerating Graph Neural Networks Training. ASPLOS (2) 2024: 683-698 - [c19]Deniz Gurevin, Mohsin Shan, Shaoyi Huang, Md Amit Hasan, Caiwen Ding, Omer Khan:
PruneGNN: Algorithm-Architecture Pruning Framework for Graph Neural Network Acceleration. HPCA 2024: 108-123 - [d2]Hongwu Peng, Xi Xie, Kaustubh Shivdikar, Amit Hasan, Jiahui Zhao, Shaoyi Huang, Omer Khan, David R. Kaeli, Caiwen Ding:
ASPLOS 2024 Artifact for "MaxK-GNN: Extremely Fast GPU Kernel Design for Accelerating Graph Neural Networks Training". Version 1. Zenodo, 2024 [all versions]
- [d1]Hongwu Peng, Xi Xie, Kaustubh Shivdikar, Amit Hasan, Jiahui Zhao, Shaoyi Huang, Omer Khan, David R. Kaeli, Caiwen Ding:
ASPLOS 2024 Artifact for "MaxK-GNN: Extremely Fast GPU Kernel Design for Accelerating Graph Neural Networks Training". Version 2. Zenodo, 2024 [all versions] - [i16]Bingbing Li, Geng Yuan, Zigeng Wang, Shaoyi Huang, Hongwu Peng, Payman Behnam, Wujie Wen, Hang Liu, Caiwen Ding:
Zero-Space Cost Fault Tolerance for Transformer-based Language Models on ReRAM. CoRR abs/2401.11664 (2024) - [i15]Kaleel Mahmood, Shaoyi Huang:
Enhanced Computationally Efficient Long LoRA Inspired Perceiver Architectures for Auto-Regressive Language Modeling. CoRR abs/2412.06106 (2024) - [i14]Zhendong Mi, Renming Zheng, Haowen Zhong, Yue Sun, Shaoyi Huang:
PromptV: Leveraging LLM-powered Multi-Agent Prompting for High-quality Verilog Generation. CoRR abs/2412.11014 (2024) - 2023
- [c18]Shaoyi Huang, Haowen Fang, Kaleel Mahmood, Bowen Lei, Nuo Xu, Bin Lei, Yue Sun, Dongkuan Xu, Wujie Wen, Caiwen Ding:
Neurogenesis Dynamics-inspired Spiking Neural Network Training Acceleration. DAC 2023: 1-6 - [c17]Shaoyi Huang, Bowen Lei, Dongkuan Xu, Hongwu Peng, Yue Sun, Mimi Xie, Caiwen Ding:
Dynamic Sparse Training via Balancing the Exploration-Exploitation Trade-off. DAC 2023: 1-6 - [c16]Xi Xie, Hongwu Peng, Amit Hasan, Shaoyi Huang, Jiahui Zhao, Haowen Fang, Wei Zhang, Tong Geng, Omer Khan, Caiwen Ding:
Accel-GCN: High-Performance GPU Accelerator Design for Graph Convolution Networks. ICCAD 2023: 1-9 - [c15]Hongwu Peng, Shaoyi Huang, Tong Zhou, Yukui Luo, Chenghong Wang, Zigeng Wang, Jiahui Zhao, Xi Xie, Ang Li, Tony Geng, Kaleel Mahmood, Wujie Wen, Xiaolin Xu, Caiwen Ding:
AutoReP: Automatic ReLU Replacement for Fast Private Network Inference. ICCV 2023: 5155-5165 - [c14]Bingbing Li, Zigeng Wang, Shaoyi Huang, Mikhail A. Bragin, Ji Li, Caiwen Ding:
Towards Lossless Head Pruning through Automatic Peer Distillation for Language Models. IJCAI 2023: 5113-5121 - [c13]Hongwu Peng, Ran Ran, Yukui Luo, Jiahui Zhao, Shaoyi Huang, Kiran Thorat, Tong Geng, Chenghong Wang, Xiaolin Xu, Wujie Wen, Caiwen Ding:
LinGCN: Structural Linearized Graph Convolutional Network for Homomorphically Encrypted Inference. NeurIPS 2023 - [i13]Hongwu Peng, Shanglin Zhou, Yukui Luo, Nuo Xu, Shijin Duan, Ran Ran, Jiahui Zhao, Shaoyi Huang, Xi Xie, Chenghong Wang, Tong Geng, Wujie Wen, Xiaolin Xu, Caiwen Ding:
RRNet: Towards ReLU-Reduced Neural Network for Two-party Computation Based Private Inference. CoRR abs/2302.02292 (2023) - [i12]Shaoyi Huang, Haowen Fang, Kaleel Mahmood, Bowen Lei, Nuo Xu, Bin Lei, Yue Sun, Dongkuan Xu, Wujie Wen, Caiwen Ding:
Neurogenesis Dynamics-inspired Spiking Neural Network Training Acceleration. CoRR abs/2304.12214 (2023) - [i11]Hongwu Peng, Shaoyi Huang, Tong Zhou, Yukui Luo, Chenghong Wang, Zigeng Wang, Jiahui Zhao, Xi Xie, Ang Li, Tony Geng, Kaleel Mahmood, Wujie Wen, Xiaolin Xu, Caiwen Ding:
AutoReP: Automatic ReLU Replacement for Fast Private Network Inference. CoRR abs/2308.10134 (2023) - [i10]Xi Xie, Hongwu Peng, Amit Hasan, Shaoyi Huang, Jiahui Zhao, Haowen Fang, Wei Zhang, Tong Geng, Omer Khan, Caiwen Ding:
Accel-GCN: High-Performance GPU Accelerator Design for Graph Convolution Networks. CoRR abs/2308.11825 (2023) - [i9]Hongwu Peng, Ran Ran, Yukui Luo, Jiahui Zhao, Shaoyi Huang, Kiran Thorat, Tong Geng, Chenghong Wang, Xiaolin Xu, Wujie Wen, Caiwen Ding:
LinGCN: Structural Linearized Graph Convolutional Network for Homomorphically Encrypted Inference. CoRR abs/2309.14331 (2023) - [i8]Hongwu Peng, Xi Xie, Kaustubh Shivdikar, Md Amit Hasan, Jiahui Zhao, Shaoyi Huang, Omer Khan, David R. Kaeli, Caiwen Ding:
MaxK-GNN: Towards Theoretical Speed Limits for Accelerating Graph Neural Networks Training. CoRR abs/2312.08656 (2023) - 2022
- [c12]Shaoyi Huang, Dongkuan Xu, Ian En-Hsu Yen, Yijue Wang, Sung-En Chang, Bingbing Li, Shiyang Chen, Mimi Xie, Sanguthevar Rajasekaran, Hang Liu, Caiwen Ding:
Sparse Progressive Distillation: Resolving Overfitting under Pretrain-and-Finetune Paradigm. ACL (1) 2022: 190-200 - [c11]Yijue Wang, Nuo Xu, Shaoyi Huang, Kaleel Mahmood, Dan Guo, Caiwen Ding, Wujie Wen, Sanguthevar Rajasekaran:
Analyzing and Defending against Membership Inference Attacks in Natural Language Processing Classification. IEEE Big Data 2022: 5823-5832 - [c10]Hongwu Peng, Shaoyi Huang, Shiyang Chen, Bingbing Li, Tong Geng, Ang Li, Weiwen Jiang, Wujie Wen, Jinbo Bi, Hang Liu, Caiwen Ding:
A length adaptive algorithm-hardware co-design of transformer on FPGA through sparse attention and dynamic pipelining. DAC 2022: 1135-1140 - [c9]Hongwu Peng, Deniz Gurevin, Shaoyi Huang, Tong Geng, Weiwen Jiang, Omer Khan, Caiwen Ding:
Towards Sparsification of Graph Neural Networks. ICCD 2022: 272-279 - [c8]Yixuan Luo, Payman Behnam, Kiran Thorat, Zhuo Liu, Hongwu Peng, Shaoyi Huang, Shu Zhou, Omer Khan, Alexey Tumanov, Caiwen Ding, Tong Geng:
CoDG-ReRAM: An Algorithm-Hardware Co-design to Accelerate Semi-Structured GNNs on ReRAM. ICCD 2022: 280-289 - [c7]Shaoyi Huang, Ning Liu, Yueying Liang, Hongwu Peng, Hongjia Li, Dongkuan Xu, Mimi Xie, Caiwen Ding:
An Automatic and Efficient BERT Pruning for Edge AI Systems. ISQED 2022: 1-6 - [i7]Shaoyi Huang, Ning Liu, Yueying Liang, Hongwu Peng, Hongjia Li, Dongkuan Xu, Mimi Xie, Caiwen Ding:
An Automatic and Efficient BERT Pruning for Edge AI Systems. CoRR abs/2206.10461 (2022) - [i6]Hongwu Peng, Shaoyi Huang, Shiyang Chen, Bingbing Li, Tong Geng, Ang Li, Weiwen Jiang, Wujie Wen, Jinbo Bi, Hang Liu, Caiwen Ding:
A Length Adaptive Algorithm-Hardware Co-design of Transformer on FPGA Through Sparse Attention and Dynamic Pipelining. CoRR abs/2208.03646 (2022) - [i5]Hongwu Peng, Deniz Gurevin, Shaoyi Huang, Tong Geng, Weiwen Jiang, Omer Khan, Caiwen Ding:
Towards Sparsification of Graph Neural Networks. CoRR abs/2209.04766 (2022) - [i4]Bin Lei, Shaoyi Huang, Caiwen Ding, Monika Filipovska:
Efficient Traffic State Forecasting using Spatio-Temporal Network Dependencies: A Sparse Graph Neural Network Approach. CoRR abs/2211.03033 (2022) - [i3]Shaoyi Huang, Bowen Lei, Dongkuan Xu, Hongwu Peng, Yue Sun, Mimi Xie, Caiwen Ding:
Dynamic Sparse Training via Balancing the Exploration-Exploitation Trade-off. CoRR abs/2211.16667 (2022) - 2021
- [c6]Panjie Qi, Yuhong Song, Hongwu Peng, Shaoyi Huang, Qingfeng Zhuge, Edwin Hsing-Mean Sha:
Accommodating Transformer onto FPGA: Coupling the Balanced Model Compression and FPGA-Implementation Optimization. ACM Great Lakes Symposium on VLSI 2021: 163-168 - [c5]Shaoyi Huang, Shiyang Chen, Hongwu Peng, Daniel Manu, Zhenglun Kong, Geng Yuan, Lei Yang, Shusen Wang, Hang Liu, Caiwen Ding:
HMC-TRAN: A Tensor-core Inspired Hierarchical Model Compression for Transformer-based DNNs on GPU. ACM Great Lakes Symposium on VLSI 2021: 169-174 - [c4]Daniel Manu, Shaoyi Huang, Caiwen Ding, Lei Yang:
Co-Exploration of Graph Neural Network and Network-on-Chip Design Using AutoML. ACM Great Lakes Symposium on VLSI 2021: 175-180 - [c3]Panjie Qi, Edwin Hsing-Mean Sha, Qingfeng Zhuge, Hongwu Peng, Shaoyi Huang, Zhenglun Kong, Yuhong Song, Bingbing Li:
Accelerating Framework of Transformer by Hardware Design and Model Compression Co-Optimization. ICCAD 2021: 1-9 - [c2]Hongwu Peng, Shaoyi Huang, Tong Geng, Ang Li, Weiwen Jiang, Hang Liu, Shusen Wang, Caiwen Ding:
Accelerating Transformer-based Deep Learning Models on FPGAs using Column Balanced Block Pruning. ISQED 2021: 142-148 - [c1]Shiyang Chen, Shaoyi Huang, Santosh Pandey, Bingbing Li, Guang R. Gao, Long Zheng, Caiwen Ding, Hang Liu:
E.T.: re-thinking self-attention for transformer models on GPUs. SC 2021: 25 - [i2]Shaoyi Huang, Dongkuan Xu, Ian En-Hsu Yen, Sung-En Chang, Bingbing Li, Shiyang Chen, Mimi Xie, Hang Liu, Caiwen Ding:
Sparse Progressive Distillation: Resolving Overfitting under Pretrain-and-Finetune Paradigm. CoRR abs/2110.08190 (2021) - [i1]Panjie Qi, Edwin Hsing-Mean Sha, Qingfeng Zhuge, Hongwu Peng, Shaoyi Huang, Zhenglun Kong, Yuhong Song, Bingbing Li:
Accelerating Framework of Transformer by Hardware Design and Model Compression Co-Optimization. CoRR abs/2110.10030 (2021)
Coauthor Index
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