Caiwen Ding - RankMe

237 papers A* 34A 27B 6C 8Misc 1Journal 122Unranked 39

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	GSR-GNN: Training Acceleration and Memory-Saving Framework of Deep GNNs on Circuit Graph. CoRR Yuebo Luo, Shiyang Li, Yifei Feng, Vishal Kancharla, Shaoyi Huang, Caiwen Ding
2026	—	`conf`	HDLxGraph: Bridging Large Language Models and HDL Repositories via HDL Graph Databases. ASP-DAC Pingqing Zheng, Jiayin Qin, Fuqi Zhang, Niraj Chitla, Zishen Wan, Shang Wu, Yu Kevin Cao, Caiwen Ding, Yang Katie Zhao
2026	J	`jnl`	HoloGraph: All-Optical Graph Learning via Light Diffraction. CoRR Yingjie Li, Shanglin Zhou, Caiwen Ding, Cunxi Yu
2026	J	`jnl`	StitchCUDA: An Automated Multi-Agents End-to-End GPU Programing Framework with Rubric-based Agentic Reinforcement Learning. CoRR Shiyang Li, Zijian Zhang, Winson Chen, Yuebo Luo, Mingyi Hong, Caiwen Ding
2025	J	`jnl`	A unified DNN weight compression framework using reweighted optimization methods. Intell. Syst. Appl. Mengchen Fan, Tianyun Zhang, Xiaolong Ma, Jiacheng Guo, Zheng Zhan, Shanglin Zhou, Minghai Qin, Caiwen Ding, Baocheng Geng, Makan Fardad, Yanzhi Wang
2025	A*	`conf`	Advancing Adversarial Robustness in GNeRFs: The IL2-NeRF Attack. CVPR Nicole Meng, Caleb Manicke, Ronak Sahu, Caiwen Ding, Yingjie Lao
2025	J	`jnl`	Attacking all tasks at once using adversarial examples in multi-task learning. Neurocomputing Lijun Zhang, Xiao Liu, Kaleel Mahmood, Caiwen Ding, Hui Guan
2025	J	`jnl`	Attacking the spike: On the security of spiking neural networks to adversarial examples. Neurocomputing Nuo Xu, Kaleel Mahmood, Haowen Fang, Ethan Rathbun, Caiwen Ding, Wujie Wen
2025	J	`jnl`	Beyond Code Pairs: Dialogue-Based Data Generation for LLM Code Translation. CoRR Le Chen, Nuo Xu, Winson Chen, Bin Lei, Pei-Hung Lin, Dunzhi Zhou, Rajeev Thakur, Caiwen Ding, Ali Jannesari, Chunhua Liao
2025	J	`jnl`	CudaForge: An Agent Framework with Hardware Feedback for CUDA Kernel Optimization. CoRR Zijian Zhang, Rong Wang, Shiyang Li, Yuebo Luo, Mingyi Hong, Caiwen Ding
2025	A	`conf`	DR-CircuitGNN: Training Acceleration of Heterogeneous Circuit Graph Neural Network on GPUs. ICS Yuebo Luo, Shiyang Li, Junran Tao, Kiran Gautam Thorat, Xi Xie, Hongwu Peng, Nuo Xu, Caiwen Ding, Shaoyi Huang
2025	J	`jnl`	DR-CircuitGNN: Training Acceleration of Heterogeneous Circuit Graph Neural Network on GPUs. CoRR Yuebo Luo, Shiyang Li, Junran Tao, Kiran Thorat, Xi Xie, Hongwu Peng, Nuo Xu, Caiwen Ding, Shaoyi Huang
2025	J	`jnl`	End-to-End On-Device Quantization-Aware Training for LLMs at Inference Cost. CoRR Qitao Tan, Xiaoying Song, Jin Lu, Guoming Li, Jun Liu, Lingzi Hong, Caiwen Ding, Jundong Li, Xiaoming Zhai, Shaoyi Huang, Wei Niu, Geng Yuan
2025	J	`jnl`	FHE-Agent: Automating CKKS Configuration for Practical Encrypted Inference via an LLM-Guided Agentic Framework. CoRR Nuo Xu, Zhaoting Gong, Ran Ran, Jinwei Tang, Wujie Wen, Caiwen Ding
2025	A	`conf`	GROOT: Graph Edge Re-growth and Partitioning for the Verification of Large Designs in Logic Synthesis. ICCAD Kiran Thorat, Hongwu Peng, Yuebo Luo, Xi Xie, Shaoyi Huang, Amit Hasan, Jiahui Zhao, Yingjie Li, Zhijie Shi, Cunxi Yu, Caiwen Ding
2025	J	`jnl`	GROOT: Graph Edge Re-growth and Partitioning for the Verification of Large Designs in Logic Synthesis. CoRR Kiran Thorat, Hongwu Peng, Yuebo Luo, Xi Xie, Shaoyi Huang, Amit Hasan, Jiahui Zhao, Yingjie Li, Zhijie Shi, Cunxi Yu, Caiwen Ding
2025	J	`jnl`	GUI-Spotlight: Adaptive Iterative Focus Refinement for Enhanced GUI Visual Grounding. CoRR Bin Lei, Nuo Xu, Ali Payani, Ming-Yi Hong, Chunhua Liao, Yu Cao, Caiwen Ding
2025	J	`jnl`	Game Theoretic Mixed Experts for Combinational Adversarial Machine Learning. IEEE Access Kaleel Mahmood, Ethan Rathbun, Ronak Sahu, Marten van Dijk, Sohaib Ahmad, Caiwen Ding
2025	A	`conf`	Graph Convolutional Network Acceleration Using Adiabatic Superconductor Josephson Devices. ICS Zhengang Li, Hongwu Peng, Xuan Shen, Masoud Zabihi, Xi Xie, Geng Yuan, Yanzhi Wang, Olivia Chen, Caiwen Ding
2025	J	`jnl`	GuirlVG: Incentivize GUI Visual Grounding via Empirical Exploration on Reinforcement Learning. CoRR Weitai Kang, Bin Lei, Gaowen Liu, Caiwen Ding, Yan Yan
2025	J	`jnl`	HDLxGraph: Bridging Large Language Models and HDL Repositories via HDL Graph Databases. CoRR Pingqing Zheng, Jiayin Qin, Fuqi Zhang, Shang Wu, Yu Cao, Caiwen Ding, Yang Zhao
2025	A	`conf`	HEDWIG: Homomorphic Encryption Accelerator Design Using BFV-HPS With HiGh-Speed Fixed-Point Approximation. FPGA Antian Wang, Weihang Tan, Zhenyu Xu, Tao Wei, Caiwen Ding, Keshab K. Parhi, Yingjie Lao
2025	J	`jnl`	InfantAgent-Next: A Multimodal Generalist Agent for Automated Computer Interaction. CoRR Bin Lei, Weitai Kang, Zijian Zhang, Winson Chen, Xi Xie, Shan Zuo, Mimi Xie, Ali Payani, Mingyi Hong, Yan Yan, Caiwen Ding
2025	—	`conf`	LLM-VeriPPA: Power, Performance, and Area Optimization aware Verilog Code Generation with Large Language Models. MLCAD Kiran Thorat, Jiahui Zhao, Yaotian Liu, Amit Hasan, Hongwu Peng, Xi Xie, Bin Lei, Caiwen Ding
2025	J	`jnl`	LLM-VeriPPA: Power, Performance, and Area Optimization aware Verilog Code Generation with Large Language Models. CoRR Kiran Thorat, Jiahui Zhao, Yaotian Liu, Amit Hasan, Hongwu Peng, Xi Xie, Bin Lei, Caiwen Ding
2025	A	`conf`	MAHL: Multi-Agent LLM-Guided Hierarchical Chiplet Design with Adaptive Debugging. ICCAD Jinwei Tang, Jiayin Qin, Nuo Xu, Pragnya Sudershan Nalla, Yu Cao, Yang Katie Zhao, Caiwen Ding
2025	J	`jnl`	MAHL: Multi-Agent LLM-Guided Hierarchical Chiplet Design with Adaptive Debugging. CoRR Jinwei Tang, Jiayin Qin, Nuo Xu, Pragnya Sudershan Nalla, Yu Cao, Yang Zhao, Caiwen Ding
2025	J	`jnl`	Observer-Based Data-Driven Consensus Control for Nonlinear Multi-Agent Systems against DoS and FDI attacks. CoRR Yi Zhang, Bin Lei, Mohamadamin Rajabinezhad, Caiwen Ding, Shan Zuo
2025	—	`conf`	Position-Enhanced Gradient Attack (PEGA) on Medical Language Models. MMAsia Nuo Xu, Christopher Stanley, John Gounley, Heidi A. Hanson, Chang Ge, Caiwen Ding
2025	A*	`conf`	RTop-K: Ultra-Fast Row-Wise Top-K Selection for Neural Network Acceleration on GPUs. ICLR Xi Xie, Yuebo Luo, Hongwu Peng, Caiwen Ding
2025	—	`conf`	RankFlow: A Multi-Role Collaborative Reranking Workflow Utilizing Large Language Models. WWW (Companion Volume) Can Jin, Hongwu Peng, Anxiang Zhang, Nuo Chen, Jiahui Zhao, Xi Xie, Kuangzheng Li, Shuya Feng, Kai Zhong, Caiwen Ding, Dimitris N. Metaxas
2025	J	`jnl`	RankFlow: A Multi-Role Collaborative Reranking Workflow Utilizing Large Language Models. CoRR Can Jin, Hongwu Peng, Anxiang Zhang, Nuo Chen, Jiahui Zhao, Xi Xie, Kuangzheng Li, Shuya Feng, Kai Zhong, Caiwen Ding, Dimitris N. Metaxas
2025	B	`conf`	TROJAN-GUARD: Hardware Trojans Detection Using GNN in RTL Designs. IJCNN Kiran Thorat, Amit Hasan, Caiwen Ding, Zhijie Shi
2025	J	`jnl`	TROJAN-GUARD: Hardware Trojans Detection Using GNN in RTL Designs. CoRR Kiran Thorat, Amit Hasan, Caiwen Ding, Zhijie Shi
2024	J	`jnl`	A Multi-Agent Reinforcement Learning Approach for Safe and Efficient Behavior Planning of Connected Autonomous Vehicles. IEEE Trans. Intell. Transp. Syst. Songyang Han, Shanglin Zhou, Jiangwei Wang, Lynn Pepin, Caiwen Ding, Jie Fu, Fei Miao
2024	—	`conf`	AdaDiff: Accelerating Diffusion Models Through Step-Wise Adaptive Computation. ECCV (79) Shengkun Tang, Yaqing Wang, Caiwen Ding, Yi Liang, Yao Li, Dongkuan Xu
2024	A	`conf`	AdaPI: Facilitating DNN Model Adaptivity for Efficient Private Inference in Edge Computing. ICCAD Tong Zhou, Jiahui Zhao, Yukui Luo, Xi Xie, Wujie Wen, Caiwen Ding, Xiaolin Xu
2024	J	`jnl`	AdaPI: Facilitating DNN Model Adaptivity for Efficient Private Inference in Edge Computing. CoRR Tong Zhou, Jiahui Zhao, Yukui Luo, Xi Xie, Wujie Wen, Caiwen Ding, Xiaolin Xu
2024	J	`jnl`	Collaborative Multi-Object Tracking With Conformal Uncertainty Propagation. IEEE Robotics Autom. Lett. Sanbao Su, Songyang Han, Yiming Li, Zhili Zhang, Chen Feng, Caiwen Ding, Fei Miao
2024	—	`conf`	Evaluating Emerging AI/ML Accelerators: IPU, RDU, and NVIDIA/AMD GPUs. ICPE (Companion) Hongwu Peng, Caiwen Ding, Tong Geng, Sutanay Choudhury, Kevin J. Barker, Ang Li
2024	J	`jnl`	Exploiting Intrinsic Redundancies in Dynamic Graph Neural Networks for Processing Efficiency. IEEE Comput. Archit. Lett. Deniz Gurevin, Caiwen Ding, Omer Khan
2024	J	`jnl`	FlashVideo: A Framework for Swift Inference in Text-to-Video Generation. CoRR Bin Lei, Le Chen, Caiwen Ding
2024	J	`jnl`	Fortran2CPP: Automating Fortran-to-C++ Migration using LLMs via Multi-Turn Dialogue and Dual-Agent Integration. CoRR Le Chen, Bin Lei, Dunzhi Zhou, Pei-Hung Lin, Chunhua Liao, Caiwen Ding, Ali Jannesari
2024	J	`jnl`	HiVeGen - Hierarchical LLM-based Verilog Generation for Scalable Chip Design. CoRR Jinwei Tang, Jiayin Qin, Kiran Thorat, Chen Tian, Yu Cao, Yang Zhao, Caiwen Ding
2024	J	`jnl`	International Trade Flow Prediction with Bilateral Trade Provisions. CoRR Zijie Pan, Stepan Gordeev, Jiahui Zhao, Ziyi Meng, Caiwen Ding, Sandro Steinbach, Dongjin Song
2024	J	`jnl`	Key Information Retrieval to Classify the Unstructured Data Content of Preferential Trade Agreements. CoRR Jiahui Zhao, Ziyi Meng, Stepan Gordeev, Zijie Pan, Dongjin Song, Sandro Steinbach, Caiwen Ding
2024	A*	`conf`	MACM: Utilizing a Multi-Agent System for Condition Mining in Solving Complex Mathematical Problems. NeurIPS Bin Lei, Yi Zhang, Shan Zuo, Ali Payani, Caiwen Ding
2024	—	`conf`	MaxK-GNN: Extremely Fast GPU Kernel Design for Accelerating Graph Neural Networks Training. ASPLOS (2) Hongwu Peng, Xi Xie, Kaustubh Shivdikar, Md Amit Hasan, Jiahui Zhao, Shaoyi Huang, Omer Khan, David R. Kaeli, Caiwen Ding
2024	A*	`conf`	PruneGNN: Algorithm-Architecture Pruning Framework for Graph Neural Network Acceleration. HPCA Deniz Gurevin, Mohsin Shan, Shaoyi Huang, Md Amit Hasan, Caiwen Ding, Omer Khan
2024	A	`conf`	Quasar-ViT: Hardware-Oriented Quantization-Aware Architecture Search for Vision Transformers. ICS Zhengang Li, Alec Lu, Yanyue Xie, Zhenglun Kong, Mengshu Sun, Hao Tang, Zhong Jia Xue, Peiyan Dong, Caiwen Ding, Yanzhi Wang, Xue Lin, Zhenman Fang
2024	J	`jnl`	Quasar-ViT: Hardware-Oriented Quantization-Aware Architecture Search for Vision Transformers. CoRR Zhengang Li, Alec Lu, Yanyue Xie, Zhenglun Kong, Mengshu Sun, Hao Tang, Zhong Jia Xue, Peiyan Dong, Caiwen Ding, Yanzhi Wang, Xue Lin, Zhenman Fang
2024	J	`jnl`	SSNet: A Lightweight Multi-Party Computation Scheme for Practical Privacy-Preserving Machine Learning Service in the Cloud. CoRR Shijin Duan, Chenghong Wang, Hongwu Peng, Yukui Luo, Wujie Wen, Caiwen Ding, Xiaolin Xu
2024	A	`conf`	SuperFlow: A Fully-Customized RTL-to-GDS Design Automation Flow for Adiabatic Quantum- Flux - Parametron Superconducting Circuits. DATE Yanyue Xie, Peiyan Dong, Geng Yuan, Zhengang Li, Masoud Zabihi, Chao Wu, Sung-En Chang, Xufeng Zhang, Xue Lin, Caiwen Ding, Nobuyuki Yoshikawa, Olivia Chen, Yanzhi Wang
2024	J	`jnl`	SuperFlow: A Fully-Customized RTL-to-GDS Design Automation Flow for Adiabatic Quantum-Flux-Parametron Superconducting Circuits. CoRR Yanyue Xie, Peiyan Dong, Geng Yuan, Zhengang Li, Masoud Zabihi, Chao Wu, Sung-En Chang, Xufeng Zhang, Xue Lin, Caiwen Ding, Nobuyuki Yoshikawa, Olivia Chen, Yanzhi Wang
2024	J	`jnl`	Theoretical Corrections and the Leveraging of Reinforcement Learning to Enhance Triangle Attack. CoRR Nicole Meng, Caleb Manicke, David Chen, Yingjie Lao, Caiwen Ding, Pengyu Hong, Kaleel Mahmood
2024	J	`jnl`	Weakly Supervised Change Detection via Knowledge Distillation and Multiscale Sigmoid Inference. CoRR Binghao Lu, Caiwen Ding, Jinbo Bi, Dongjin Song
2024	J	`jnl`	Zero-Space Cost Fault Tolerance for Transformer-based Language Models on ReRAM. CoRR Bingbing Li, Geng Yuan, Zigeng Wang, Shaoyi Huang, Hongwu Peng, Payman Behnam, Wujie Wen, Hang Liu, Caiwen Ding
2023	—	`conf`	A Deep Learning Approach for Ventricular Arrhythmias Classification using Microcontroller. ISQED Ya-sine Agrignan, Shanglin Zhou, Jun Bai, Sahidul Islam, Sheida Nabavi, Mimi Xie, Caiwen Ding
2023	A*	`conf`	AQ2PNN: Enabling Two-party Privacy-Preserving Deep Neural Network Inference with Adaptive Quantization. MICRO Yukui Luo, Nuo Xu, Hongwu Peng, Chenghong Wang, Shijin Duan, Kaleel Mahmood, Wujie Wen, Caiwen Ding, Xiaolin Xu
2023	A	`conf`	Accel-GCN: High-Performance GPU Accelerator Design for Graph Convolution Networks. ICCAD Xi Xie, Hongwu Peng, Amit Hasan, Shaoyi Huang, Jiahui Zhao, Haowen Fang, Wei Zhang, Tong Geng, Omer Khan, Caiwen Ding
2023	J	`jnl`	Accel-GCN: High-Performance GPU Accelerator Design for Graph Convolution Networks. CoRR Xi Xie, Hongwu Peng, Amit Hasan, Shaoyi Huang, Jiahui Zhao, Haowen Fang, Wei Zhang, Tong Geng, Omer Khan, Caiwen Ding
2023	A*	`conf`	Accelerating Dataset Distillation via Model Augmentation. CVPR Lei Zhang, Jie Zhang, Bowen Lei, Subhabrata Mukherjee, Xiang Pan, Bo Zhao, Caiwen Ding, Yao Li, Dongkuan Xu
2023	J	`jnl`	Advanced Large Language Model (LLM)-Driven Verilog Development: Enhancing Power, Performance, and Area Optimization in Code Synthesis. CoRR Kiran Thorat, Jiahui Zhao, Yaotian Liu, Hongwu Peng, Xi Xie, Bin Lei, Jeff Zhang, Caiwen Ding
2023	A*	`conf`	AutoReP: Automatic ReLU Replacement for Fast Private Network Inference. ICCV 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
2023	J	`jnl`	AutoReP: Automatic ReLU Replacement for Fast Private Network Inference. CoRR 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
2023	—	`conf`	Automatic Subnetwork Search Through Dynamic Differentiable Neuron Pruning. ISQED Zigeng Wang, Bingbing Li, Xia Xiao, Tianyun Zhang, Mikhail A. Bragin, Bing Yan, Caiwen Ding, Sanguthevar Rajasekaran
2023	J	`jnl`	Boosting Logical Reasoning in Large Language Models through a New Framework: The Graph of Thought. CoRR Bin Lei, Pei-Hung Lin, Chunhua Liao, Caiwen Ding
2023	J	`jnl`	Collaborative Multi-Object Tracking with Conformal Uncertainty Propagation. CoRR Sanbao Su, Songyang Han, Yiming Li, Zhili Zhang, Chen Feng, Caiwen Ding, Fei Miao
2023	A*	`conf`	Condense: A Framework for Device and Frequency Adaptive Neural Network Models on the Edge. DAC Yifan Gong, Pu Zhao, Zheng Zhan, Yushu Wu, Chao Wu, Zhenglun Kong, Minghai Qin, Caiwen Ding, Yanzhi Wang
2023	—	`conf`	Creating a Dataset for High-Performance Computing Code Translation using LLMs: A Bridge Between OpenMP Fortran and C++. HPEC Bin Lei, Caiwen Ding, Le Chen, Pei-Hung Lin, Chunhua Liao
2023	J	`jnl`	Creating a Dataset for High-Performance Computing Code Translation: A Bridge Between HPC Fortran and C++. CoRR Bin Lei, Caiwen Ding, Le Chen, Pei-Hung Lin, Chunhua Liao
2023	J	`jnl`	DeeDiff: Dynamic Uncertainty-Aware Early Exiting for Accelerating Diffusion Model Generation. CoRR Shengkun Tang, Yaqing Wang, Caiwen Ding, Yi Liang, Yao Li, Dongkuan Xu
2023	J	`jnl`	Dynamic Gradient Balancing for Enhanced Adversarial Attacks on Multi-Task Models. CoRR Lijun Zhang, Xiao Liu, Kaleel Mahmood, Caiwen Ding, Hui Guan
2023	A*	`conf`	Dynamic Sparse Training via Balancing the Exploration-Exploitation Trade-off. DAC Shaoyi Huang, Bowen Lei, Dongkuan Xu, Hongwu Peng, Yue Sun, Mimi Xie, Caiwen Ding
2023	J	`jnl`	Evaluating Emerging AI/ML Accelerators: IPU, RDU, and NVIDIA/AMD GPUs. CoRR Hongwu Peng, Caiwen Ding, Tong Geng, Sutanay Choudhury, Kevin J. Barker, Ang Li
2023	A*	`conf`	Ising-CF: A Pathbreaking Collaborative Filtering Method Through Efficient Ising Machine Learning. DAC Zhuo Liu, Yunan Yang, Zhenyu Pan, Anshujit Sharma, Amit Hasan, Caiwen Ding, Ang Li, Michael C. Huang, Tong Geng
2023	A*	`conf`	LinGCN: Structural Linearized Graph Convolutional Network for Homomorphically Encrypted Inference. NeurIPS Hongwu Peng, Ran Ran, Yukui Luo, Jiahui Zhao, Shaoyi Huang, Kiran Thorat, Tong Geng, Chenghong Wang, Xiaolin Xu, Wujie Wen, Caiwen Ding
2023	J	`jnl`	LinGCN: Structural Linearized Graph Convolutional Network for Homomorphically Encrypted Inference. CoRR Hongwu Peng, Ran Ran, Yukui Luo, Jiahui Zhao, Shaoyi Huang, Kiran Thorat, Tong Geng, Chenghong Wang, Xiaolin Xu, Wujie Wen, Caiwen Ding
2023	J	`jnl`	MaxK-GNN: Towards Theoretical Speed Limits for Accelerating Graph Neural Networks Training. CoRR Hongwu Peng, Xi Xie, Kaustubh Shivdikar, Md Amit Hasan, Jiahui Zhao, Shaoyi Huang, Omer Khan, David R. Kaeli, Caiwen Ding
2023	J	`jnl`	Memristor-Based Spectral Decomposition of Matrices and Its Applications. IEEE Trans. Computers Zeinab S. Jalali, Chenghong Wang, Griffin Kearney, Geng Yuan, Caiwen Ding, Yinan Zhou, Yanzhi Wang, Sucheta Soundarajan
2023	B	`conf`	MergePath-SpMM: Parallel Sparse Matrix-Matrix Algorithm for Graph Neural Network Acceleration. ISPASS Mohsin Shan, Deniz Gurevin, Jared Nye, Caiwen Ding, Omer Khan
2023	A*	`conf`	Neurogenesis Dynamics-inspired Spiking Neural Network Training Acceleration. DAC Shaoyi Huang, Haowen Fang, Kaleel Mahmood, Bowen Lei, Nuo Xu, Bin Lei, Yue Sun, Dongkuan Xu, Wujie Wen, Caiwen Ding
2023	J	`jnl`	Neurogenesis Dynamics-inspired Spiking Neural Network Training Acceleration. CoRR Shaoyi Huang, Haowen Fang, Kaleel Mahmood, Bowen Lei, Nuo Xu, Bin Lei, Yue Sun, Dongkuan Xu, Wujie Wen, Caiwen Ding
2023	A*	`conf`	PASNet: Polynomial Architecture Search Framework for Two-party Computation-based Secure Neural Network Deployment. DAC Hongwu Peng, Shanglin Zhou, Yukui Luo, Nuo Xu, Shijin Duan, Ran Ran, Jiahui Zhao, Chenghong Wang, Tong Geng, Wujie Wen, Xiaolin Xu, Caiwen Ding
2023	J	`jnl`	PASNet: Polynomial Architecture Search Framework for Two-party Computation-based Secure Neural Network Deployment. CoRR Hongwu Peng, Shanglin Zhou, Yukui Luo, Nuo Xu, Shijin Duan, Ran Ran, Jiahui Zhao, Chenghong Wang, Tong Geng, Wujie Wen, Xiaolin Xu, Caiwen Ding
2023	A*	`conf`	Physics-aware Roughness Optimization for Diffractive Optical Neural Networks. DAC Shanglin Zhou, Yingjie Li, Minhan Lou, Weilu Gao, Zhijie Shi, Cunxi Yu, Caiwen Ding
2023	J	`jnl`	Physics-aware Roughness Optimization for Diffractive Optical Neural Networks. CoRR Shanglin Zhou, Yingjie Li, Minhan Lou, Weilu Gao, Zhijie Shi, Cunxi Yu, Caiwen Ding
2023	J	`jnl`	RRNet: Towards ReLU-Reduced Neural Network for Two-party Computation Based Private Inference. CoRR 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
2023	J	`jnl`	Shared Information-Based Safe And Efficient Behavior Planning For Connected Autonomous Vehicles. CoRR Songyang Han, Shanglin Zhou, Lynn Pepin, Jiangwei Wang, Caiwen Ding, Fei Miao
2023	A*	`conf`	SpENCNN: Orchestrating Encoding and Sparsity for Fast Homomorphically Encrypted Neural Network Inference. ICML Ran Ran, Xinwei Luo, Wei Wang, Tao Liu, Gang Quan, Xiaolin Xu, Caiwen Ding, Wujie Wen
2023	A*	`conf`	Spectral-DP: Differentially Private Deep Learning through Spectral Perturbation and Filtering. SP Ce Feng, Nuo Xu, Wujie Wen, Parv Venkitasubramaniam, Caiwen Ding
2023	J	`jnl`	Spectral-DP: Differentially Private Deep Learning through Spectral Perturbation and Filtering. CoRR Ce Feng, Nuo Xu, Wujie Wen, Parv Venkitasubramaniam, Caiwen Ding
2023	J	`jnl`	Surrogate Lagrangian Relaxation: A Path To Retrain-free Deep Neural Network Pruning. CoRR Shanglin Zhou, Mikhail A. Bragin, Lynn Pepin, Deniz Gurevin, Fei Miao, Caiwen Ding
2023	J	`jnl`	Surrogate Lagrangian Relaxation: A Path to Retrain-Free Deep Neural Network Pruning. ACM Trans. Design Autom. Electr. Syst. Shanglin Zhou, Mikhail A. Bragin, Deniz Gurevin, Lynn Pepin, Fei Miao, Caiwen Ding
2023	A	`conf`	TANGO: re-thinking quantization for graph neural network training on GPUs. SC Shiyang Chen, Da Zheng, Caiwen Ding, Chengying Huan, Yuede Ji, Hang Liu
2023	J	`jnl`	Tango: rethinking quantization for graph neural network training on GPUs. CoRR Shiyang Chen, Da Zheng, Caiwen Ding, Chengying Huan, Yuede Ji, Hang Liu
2023	A*	`conf`	Towards Lossless Head Pruning through Automatic Peer Distillation for Language Models. IJCAI Bingbing Li, Zigeng Wang, Shaoyi Huang, Mikhail A. Bragin, Ji Li, Caiwen Ding
2023	J	`jnl`	Towards Zero Memory Footprint Spiking Neural Network Training. CoRR Bin Lei, Sheng Lin, Pei-Hung Lin, Chunhua Liao, Caiwen Ding
2023	A*	`conf`	Uncertainty Quantification of Collaborative Detection for Self-Driving. ICRA Sanbao Su, Yiming Li, Sihong He, Songyang Han, Chen Feng, Caiwen Ding, Fei Miao
2023	—	`conf`	Understanding Node Allocation on Leadership-Class Supercomputers with Graph Analytics. HPCC/DSS/SmartCity/DependSys Andy Trinh, Shivam Sheth, Anil Gaihre, Caiwen Ding, Jieyang Chen, Feiyi Wang, David Pugmire, Scott Klasky, Hang Liu, Lipeng Wan
2023	A*	`conf`	You Need Multiple Exiting: Dynamic Early Exiting for Accelerating Unified Vision Language Model. CVPR Shengkun Tang, Yaqing Wang, Zhenglun Kong, Tianchi Zhang, Yao Li, Caiwen Ding, Yanzhi Wang, Yi Liang, Dongkuan Xu
2022	J	`jnl`	A Length Adaptive Algorithm-Hardware Co-design of Transformer on FPGA Through Sparse Attention and Dynamic Pipelining. CoRR Hongwu Peng, Shaoyi Huang, Shiyang Chen, Bingbing Li, Tong Geng, Ang Li, Weiwen Jiang, Wujie Wen, Jinbo Bi, Hang Liu, Caiwen Ding
2022	J	`jnl`	A Secure and Efficient Federated Learning Framework for NLP. CoRR Jieren Deng, Chenghong Wang, Xianrui Meng, Yijue Wang, Ji Li, Sheng Lin, Shuo Han, Fei Miao, Sanguthevar Rajasekaran, Caiwen Ding
2022	A*	`conf`	A length adaptive algorithm-hardware co-design of transformer on FPGA through sparse attention and dynamic pipelining. DAC Hongwu Peng, Shaoyi Huang, Shiyang Chen, Bingbing Li, Tong Geng, Ang Li, Weiwen Jiang, Wujie Wen, Jinbo Bi, Hang Liu, Caiwen Ding
2022	J	`jnl`	Accelerating Dataset Distillation via Model Augmentation. CoRR Lei Zhang, Jie Zhang, Bowen Lei, Subhabrata Mukherjee, Xiang Pan, Bo Zhao, Caiwen Ding, Yao Li, Dongkuan Xu
2022	J	`jnl`	Aerial Manipulation Using a Novel Unmanned Aerial Vehicle Cyber-Physical System. CoRR Caiwu Ding, Hongwu Peng, Lu Lu, Caiwen Ding
2022	A	`conf`	All-in-One: A Highly Representative DNN Pruning Framework for Edge Devices with Dynamic Power Management. ICCAD Yifan Gong, Zheng Zhan, Pu Zhao, Yushu Wu, Chao Wu, Caiwen Ding, Weiwen Jiang, Minghai Qin, Yanzhi Wang
2022	J	`jnl`	All-in-One: A Highly Representative DNN Pruning Framework for Edge Devices with Dynamic Power Management. CoRR Yifan Gong, Zheng Zhan, Pu Zhao, Yushu Wu, Chao Wu, Caiwen Ding, Weiwen Jiang, Minghai Qin, Yanzhi Wang
2022	—	`conf`	An Automatic and Efficient BERT Pruning for Edge AI Systems. ISQED Shaoyi Huang, Ning Liu, Yueying Liang, Hongwu Peng, Hongjia Li, Dongkuan Xu, Mimi Xie, Caiwen Ding
2022	J	`jnl`	An Automatic and Efficient BERT Pruning for Edge AI Systems. CoRR Shaoyi Huang, Ning Liu, Yueying Liang, Hongwu Peng, Hongjia Li, Dongkuan Xu, Mimi Xie, Caiwen Ding
2022	—	`conf`	An Intermittent OTA Approach to Update the DL Weights on Energy Harvesting Devices. ISQED Wei Wei, Sahidul Islam, Jishnu Banerjee, Shanglin Zhou, Chen Pan, Caiwen Ding, Mimi Xie
2022	B	`conf`	Analyzing and Defending against Membership Inference Attacks in Natural Language Processing Classification. IEEE Big Data Yijue Wang, Nuo Xu, Shaoyi Huang, Kaleel Mahmood, Dan Guo, Caiwen Ding, Wujie Wen, Sanguthevar Rajasekaran
2022	C	`conf`	CoDG-ReRAM: An Algorithm-Hardware Co-design to Accelerate Semi-Structured GNNs on ReRAM. ICCD YiXuan Luo, Payman Behnam, Kiran Thorat, Zhuo Liu, Hongwu Peng, Shaoyi Huang, Shu Zhou, Omer Khan, Alexey Tumanov, Caiwen Ding, Tong Geng
2022	J	`jnl`	Dynamic Sparse Training via Balancing the Exploration-Exploitation Trade-off. CoRR Shaoyi Huang, Bowen Lei, Dongkuan Xu, Hongwu Peng, Yue Sun, Mimi Xie, Caiwen Ding
2022	A	`conf`	EVE: Environmental Adaptive Neural Network Models for Low-Power Energy Harvesting System. ICCAD Sahidul Islam, Shanglin Zhou, Ran Ran, Yufang Jin, Wujie Wen, Caiwen Ding, Mimi Xie
2022	J	`jnl`	EVE: Environmental Adaptive Neural Network Models for Low-power Energy Harvesting System. CoRR Sahidul Islam, Shanglin Zhou, Ran Ran, Yufang Jin, Wujie Wen, Caiwen Ding, Mimi Xie
2022	J	`jnl`	Efficient Traffic State Forecasting using Spatio-Temporal Network Dependencies: A Sparse Graph Neural Network Approach. CoRR Bin Lei, Shaoyi Huang, Caiwen Ding, Monika Filipovska
2022	A	`conf`	Enabling Fast Deep Learning on Tiny Energy-Harvesting IoT Devices. DATE Sahidul Islam, Jieren Deng, Shanglin Zhou, Chen Pan, Caiwen Ding, Mimi Xie
2022	J	`jnl`	Game Theoretic Mixed Experts for Combinational Adversarial Machine Learning. CoRR Ethan Rathbun, Kaleel Mahmood, Sohaib Ahmad, Caiwen Ding, Marten van Dijk
2022	J	`jnl`	Graph-Based Shape Analysis for Heterogeneous Geometric Datasets: Similarity, Retrieval and Substructure Matching. Comput. Aided Des. Jiangce Chen, Horea T. Ilies, Caiwen Ding
2022	C	`conf`	On the Design of Quantum Graph Convolutional Neural Network in the NISQ-Era and Beyond. ICCD Zhirui Hu, Jinyang Li, Zhenyu Pan, Shanglin Zhou, Lei Yang, Caiwen Ding, Omer Khan, Tong Geng, Weiwen Jiang
2022	A*	`conf`	Poster: Cryptographic Inferences for Video Deep Neural Networks. CCS Bingyu Liu, Rujia Wang, Zhongjie Ba, Shanglin Zhou, Caiwen Ding, Yuan Hong
2022	—	`conf`	QuClassi: A Hybrid Deep Neural Network Architecture based on Quantum State Fidelity. MLSys Samuel A. Stein, Betis Baheri, Daniel Chen, Ying Mao, Qiang Guan, Ang Li, Shuai Xu, Caiwen Ding
2022	C	`conf`	Reliability Improvement in RRAM-based DNN for Edge Computing. ISCAS Md. Oli-Uz-Zaman, Saleh Ahmad Khan, Geng Yuan, Yanzhi Wang, Zhiheng Liao, Jingyan Fu, Caiwen Ding, Jinhui Wang
2022	J	`jnl`	Securing the Spike: On the Transferabilty and Security of Spiking Neural Networks to Adversarial Examples. CoRR Nuo Xu, Kaleel Mahmood, Haowen Fang, Ethan Rathbun, Caiwen Ding, Wujie Wen
2022	—	`conf`	Sparse Progressive Distillation: Resolving Overfitting under Pretrain-and-Finetune Paradigm. ACL (1) 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
2022	C	`conf`	Towards Real-Time Temporal Graph Learning. ICCD Deniz Gurevin, Mohsin Shan, Tong Geng, Weiwen Jiang, Caiwen Ding, Omer Khan
2022	J	`jnl`	Towards Real-Time Temporal Graph Learning. CoRR Deniz Gurevin, Mohsin Shan, Tong Geng, Weiwen Jiang, Caiwen Ding, Omer Khan
2022	C	`conf`	Towards Sparsification of Graph Neural Networks. ICCD Hongwu Peng, Deniz Gurevin, Shaoyi Huang, Tong Geng, Weiwen Jiang, Omer Khan, Caiwen Ding
2022	J	`jnl`	Towards Sparsification of Graph Neural Networks. CoRR Hongwu Peng, Deniz Gurevin, Shaoyi Huang, Tong Geng, Weiwen Jiang, Omer Khan, Caiwen Ding
2022	J	`jnl`	Uncertainty Quantification of Collaborative Detection for Self-Driving. CoRR Sanbao Su, Yiming Li, Sihong He, Songyang Han, Chen Feng, Caiwen Ding, Fei Miao
2022	B	`conf`	Variance of the Gradient Also Matters: Privacy Leakage from Gradients. IJCNN Yijue Wang, Jieren Deng, Dan Guo, Chenghong Wang, Xianrui Meng, Hang Liu, Chao Shang, Binghui Wang, Qin Cao, Caiwen Ding, Sanguthevar Rajasekaran
2022	J	`jnl`	You Need Multiple Exiting: Dynamic Early Exiting for Accelerating Unified Vision Language Model. CoRR Shengkun Tang, Yaqing Wang, Zhenglun Kong, Tianchi Zhang, Yao Li, Caiwen Ding, Yanzhi Wang, Yi Liang, Dongkuan Xu
2021	A*	`conf`	A Compression-Compilation Framework for On-mobile Real-time BERT Applications. IJCAI Wei Niu, Zhenglun Kong, Geng Yuan, Weiwen Jiang, Jiexiong Guan, Caiwen Ding, Pu Zhao, Sijia Liu, Bin Ren, Yanzhi Wang
2021	J	`jnl`	A Compression-Compilation Framework for On-mobile Real-time BERT Applications. CoRR Wei Niu, Zhenglun Kong, Geng Yuan, Weiwen Jiang, Jiexiong Guan, Caiwen Ding, Pu Zhao, Sijia Liu, Bin Ren, Yanzhi Wang
2021	—	`conf`	A Secure and Efficient Federated Learning Framework for NLP. EMNLP (1) Chenghong Wang, Jieren Deng, Xianrui Meng, Yijue Wang, Ji Li, Sheng Lin, Shuo Han, Fei Miao, Sanguthevar Rajasekaran, Caiwen Ding
2021	A*	`conf`	A Unified DNN Weight Pruning Framework Using Reweighted Optimization Methods. DAC Tianyun Zhang, Xiaolong Ma, Zheng Zhan, Shanglin Zhou, Caiwen Ding, Makan Fardad, Yanzhi Wang
2021	—	`conf`	Accelerating Transformer-based Deep Learning Models on FPGAs using Column Balanced Block Pruning. ISQED Hongwu Peng, Shaoyi Huang, Tong Geng, Ang Li, Weiwen Jiang, Hang Liu, Shusen Wang, Caiwen Ding
2021	A*	`conf`	Against Membership Inference Attack: Pruning is All You Need. IJCAI Yijue Wang, Chenghong Wang, Zigeng Wang, Shanglin Zhou, Hang Liu, Jinbo Bi, Caiwen Ding, Sanguthevar Rajasekaran
2021	—	`conf`	An End-to-end Multi-task Object Detection using Embedded GPU in Autonomous Driving. ISQED Shanglin Zhou, Mimi Xie, Yufang Jin, Fei Miao, Caiwen Ding
2021	—	`conf`	Binary Complex Neural Network Acceleration on FPGA : (Invited Paper). ASAP Hongwu Peng, Shanglin Zhou, Scott Weitze, Jiaxin Li, Sahidul Islam, Tong Geng, Ang Li, Wei Zhang, Minghu Song, Mimi Xie, Hang Liu, Caiwen Ding
2021	J	`jnl`	Binary Complex Neural Network Acceleration on FPGA. CoRR Hongwu Peng, Shanglin Zhou, Scott Weitze, Jiaxin Li, Sahidul Islam, Tong Geng, Ang Li, Wei Zhang, Minghu Song, Mimi Xie, Hang Liu, Caiwen Ding
2021	—	`conf`	Co-Exploration of Graph Neural Network and Network-on-Chip Design Using AutoML. ACM Great Lakes Symposium on VLSI Daniel Manu, Shaoyi Huang, Caiwen Ding, Lei Yang
2021	A*	`conf`	Dancing along Battery: Enabling Transformer with Run-time Reconfigurability on Mobile Devices. DAC Yuhong Song, Weiwen Jiang, Bingbing Li, Panjie Qi, Qingfeng Zhuge, Edwin Hsing-Mean Sha, Sakyasingha Dasgupta, Yiyu Shi, Caiwen Ding
2021	J	`jnl`	Dancing along Battery: Enabling Transformer with Run-time Reconfigurability on Mobile Devices. CoRR Yuhong Song, Weiwen Jiang, Bingbing Li, Panjie Qi, Qingfeng Zhuge, Edwin Hsing-Mean Sha, Sakyasingha Dasgupta, Yiyu Shi, Caiwen Ding
2021	J	`jnl`	Design, Sensing, and Control of a Novel UAV Platform for Aerial Drilling and Screwing. IEEE Robotics Autom. Lett. Caiwu Ding, Lu Lu, Cong Wang, Caiwen Ding
2021	J	`jnl`	Detecting Gender Bias in Transformer-based Models: A Case Study on BERT. CoRR Bingbing Li, Hongwu Peng, Rajat Sainju, Junhuan Yang, Lei Yang, Yueying Liang, Weiwen Jiang, Binghui Wang, Hang Liu, Caiwen Ding
2021	J	`jnl`	Dr. Top-k: Delegate-Centric Top-k on GPUs. CoRR Anil Gaihre, Da Zheng, Scott Weitze, Lingda Li, Shuaiwen Leon Song, Caiwen Ding, Xiaoye S. Li, Hang Liu
2021	A	`conf`	Dr. Top-k: delegate-centric Top-k on GPUs. SC Anil Gaihre, Da Zheng, Scott Weitze, Lingda Li, Shuaiwen Leon Song, Caiwen Ding, Xiaoye S. Li, Hang Liu
2021	A	`conf`	E.T.: re-thinking self-attention for transformer models on GPUs. SC Shiyang Chen, Shaoyi Huang, Santosh Pandey, Bingbing Li, Guang R. Gao, Long Zheng, Caiwen Ding, Hang Liu
2021	A*	`conf`	Enabling Retrain-free Deep Neural Network Pruning Using Surrogate Lagrangian Relaxation. IJCAI Deniz Gurevin, Mikhail A. Bragin, Caiwen Ding, Shanglin Zhou, Lynn Pepin, Bingbing Li, Fei Miao
2021	J	`jnl`	Enabling Super-Fast Deep Learning on Tiny Energy-Harvesting IoT Devices. CoRR Sahidul Islam, Jieren Deng, Shanglin Zhou, Chen Pan, Caiwen Ding, Mimi Xie
2021	J	`jnl`	Exploration of Quantum Neural Architecture by Mixing Quantum Neuron Designs. CoRR Zhepeng Wang, Zhiding Liang, Shanglin Zhou, Caiwen Ding, Jinjun Xiong, Yiyu Shi, Weiwen Jiang
2021	A	`conf`	Exploration of Quantum Neural Architecture by Mixing Quantum Neuron Designs: (Invited Paper). ICCAD Zhepeng Wang, Zhiding Liang, Shanglin Zhou, Caiwen Ding, Yiyu Shi, Weiwen Jiang
2021	A	`conf`	FL-DISCO: Federated Generative Adversarial Network for Graph-based Molecule Drug Discovery: Special Session Paper. ICCAD Daniel Manu, Yi Sheng, Junhuan Yang, Jieren Deng, Tong Geng, Ang Li, Caiwen Ding, Weiwen Jiang, Lei Yang
2021	A*	`conf`	FORMS: Fine-grained Polarized ReRAM-based In-situ Computation for Mixed-signal DNN Accelerator. ISCA Geng Yuan, Payman Behnam, Zhengang Li, Ali Shafiee, Sheng Lin, Xiaolong Ma, Hang Liu, Xuehai Qian, Mahdi Nazm Bojnordi, Yanzhi Wang, Caiwen Ding
2021	J	`jnl`	FORMS: Fine-grained Polarized ReRAM-based In-situ Computation for Mixed-signal DNN Accelerator. CoRR Geng Yuan, Payman Behnam, Zhengang Li, Ali Shafiee, Sheng Lin, Xiaolong Ma, Hang Liu, Xuehai Qian, Mahdi Nazm Bojnordi, Yanzhi Wang, Caiwen Ding
2021	—	`conf`	HMC-TRAN: A Tensor-core Inspired Hierarchical Model Compression for Transformer-based DNNs on GPU. ACM Great Lakes Symposium on VLSI Shaoyi Huang, Shiyang Chen, Hongwu Peng, Daniel Manu, Zhenglun Kong, Geng Yuan, Lei Yang, Shusen Wang, Hang Liu, Caiwen Ding
2021	A	`conf`	Optimizing FPGA-based Accelerator Design for Large-Scale Molecular Similarity Search (Special Session Paper). ICCAD Hongwu Peng, Shiyang Chen, Zhepeng Wang, Junhuan Yang, Scott A. Weitze, Tong Geng, Ang Li, Jinbo Bi, Minghu Song, Weiwen Jiang, Hang Liu, Caiwen Ding
2021	J	`jnl`	Optimizing FPGA-based Accelerator Design for Large-Scale Molecular Similarity Search. CoRR Hongwu Peng, Shiyang Chen, Zhepeng Wang, Junhuan Yang, Scott A. Weitze, Tong Geng, Ang Li, Jinbo Bi, Minghu Song, Weiwen Jiang, Hang Liu, Caiwen Ding
2021	J	`jnl`	Sparse Progressive Distillation: Resolving Overfitting under Pretrain-and-Finetune Paradigm. CoRR Shaoyi Huang, Dongkuan Xu, Ian En-Hsu Yen, Sung-En Chang, Bingbing Li, Shiyang Chen, Mimi Xie, Hang Liu, Caiwen Ding
2021	—	`conf`	TAG: Gradient Attack on Transformer-based Language Models. EMNLP (Findings) Jieren Deng, Yijue Wang, Ji Li, Chenghong Wang, Chao Shang, Hang Liu, Sanguthevar Rajasekaran, Caiwen Ding
2021	J	`jnl`	TAG: Transformer Attack from Gradient. CoRR Jieren Deng, Yijue Wang, Ji Li, Chao Shang, Hang Liu, Sanguthevar Rajasekaran, Caiwen Ding
2021	J	`jnl`	TRUST: Triangle Counting Reloaded on GPUs. CoRR Santosh Pandey, Zhibin Wang, Sheng Zhong, Chen Tian, Bolong Zheng, Xiaoye S. Li, Lingda Li, Adolfy Hoisie, Caiwen Ding, Dong Li, Hang Liu
2021	A	`conf`	TinyADC: Peripheral Circuit-aware Weight Pruning Framework for Mixed-signal DNN Accelerators. DATE Geng Yuan, Payman Behnam, Yuxuan Cai, Ali Shafiee, Jingyan Fu, Zhiheng Liao, Zhengang Li, Xiaolong Ma, Jieren Deng, Jinhui Wang, Mahdi Nazm Bojnordi, Yanzhi Wang, Caiwen Ding
2021	J	`jnl`	Trust: Triangle Counting Reloaded on GPUs. IEEE Trans. Parallel Distributed Syst. Santosh Pandey, Zhibin Wang, Sheng Zhong, Chen Tian, Bolong Zheng, Xiaoye S. Li, Lingda Li, Adolfy Hoisie, Caiwen Ding, Dong Li, Hang Liu
2020	—	`conf`	A DNN Compression Framework for SOT-MRAM-based Processing-In-Memory Engine. SoCC Geng Yuan, Xiaolong Ma, Sheng Lin, Zhengang Li, Jieren Deng, Caiwen Ding
2020	—	`conf`	A Privacy-Preserving-Oriented DNN Pruning and Mobile Acceleration Framework. ACM Great Lakes Symposium on VLSI Yifan Gong, Zheng Zhan, Zhengang Li, Wei Niu, Xiaolong Ma, Wenhao Wang, Bin Ren, Caiwen Ding, Xue Lin, Xiaolin Xu, Yanzhi Wang
2020	J	`jnl`	A Surrogate Lagrangian Relaxation-based Model Compression for Deep Neural Networks. CoRR Deniz Gurevin, Shanglin Zhou, Lynn Pepin, Bingbing Li, Mikhail A. Bragin, Caiwen Ding, Fei Miao
2020	J	`jnl`	A Unified DNN Weight Compression Framework Using Reweighted Optimization Methods. CoRR Tianyun Zhang, Xiaolong Ma, Zheng Zhan, Shanglin Zhou, Minghai Qin, Fei Sun, Yen-Kuang Chen, Caiwen Ding, Makan Fardad, Yanzhi Wang
2020	J	`jnl`	Achieving Real-Time Execution of Transformer-based Large-scale Models on Mobile with Compiler-aware Neural Architecture Optimization. CoRR Wei Niu, Zhenglun Kong, Geng Yuan, Weiwen Jiang, Jiexiong Guan, Caiwen Ding, Pu Zhao, Sijia Liu, Bin Ren, Yanzhi Wang
2020	—	`conf`	An Efficient Deep Reinforcement Learning Framework for UAVs. ISQED Shanglin Zhou, Bingbing Li, Caiwu Ding, Lu Lu, Caiwen Ding
2020	J	`jnl`	ESMFL: Efficient and Secure Models for Federated Learning. CoRR Sheng Lin, Chenghong Wang, Hongjia Li, Jieren Deng, Yanzhi Wang, Caiwen Ding
2020	—	`conf`	Efficient Transformer-based Large Scale Language Representations using Hardware-friendly Block Structured Pruning. EMNLP (Findings) Bingbing Li, Zhenglun Kong, Tianyun Zhang, Ji Li, Zhengang Li, Hang Liu, Caiwen Ding
2020	J	`jnl`	Efficient Transformer-based Large Scale Language Representations using Hardware-friendly Block Structured Pruning. CoRR Bingbing Li, Zhenglun Kong, Tianyun Zhang, Ji Li, Zhengang Li, Hang Liu, Caiwen Ding
2020	A*	`conf`	FTDL: A Tailored FPGA-Overlay for Deep Learning with High Scalability. DAC Runbin Shi, Yuhao Ding, Xuechao Wei, He Li, Hang Liu, Hayden Kwok-Hay So, Caiwen Ding
2020	A	`conf`	FTDL: An FPGA-tailored Architecture for Deep Learning Systems. FPGA Runbin Shi, Yuhao Ding, Xuechao Wei, Hang Liu, Hayden Kwok-Hay So, Caiwen Ding
2020	J	`jnl`	FTRANS: Energy-Efficient Acceleration of Transformers using FPGA. CoRR Bingbing Li, Santosh Pandey, Haowen Fang, Yanjun Lyv, Ji Li, Jieyang Chen, Mimi Xie, Lipeng Wan, Hang Liu, Caiwen Ding
2020	A	`conf`	FTRANS: energy-efficient acceleration of transformers using FPGA. ISLPED Bingbing Li, Santosh Pandey, Haowen Fang, Yanjun Lyv, Ji Li, Jieyang Chen, Mimi Xie, Lipeng Wan, Hang Liu, Caiwen Ding
2020	J	`jnl`	MCMIA: Model Compression Against Membership Inference Attack in Deep Neural Networks. CoRR Yijue Wang, Chenghong Wang, Zigeng Wang, Shanglin Zhou, Hang Liu, Jinbo Bi, Caiwen Ding, Sanguthevar Rajasekaran
2020	J	`jnl`	SAPAG: A Self-Adaptive Privacy Attack From Gradients. CoRR Yijue Wang, Jieren Deng, Dan Guo, Chenghong Wang, Xianrui Meng, Hang Liu, Caiwen Ding, Sanguthevar Rajasekaran
2020	—	`conf`	Tiny but Accurate: A Pruned, Quantized and Optimized Memristor Crossbar Framework for Ultra Efficient DNN Implementation. ASP-DAC Xiaolong Ma, Geng Yuan, Sheng Lin, Caiwen Ding, Fuxun Yu, Tao Liu, Wujie Wen, Xiang Chen, Yanzhi Wang
2020	Misc	`conf`	Towards an Efficient and General Framework of Robust Training for Graph Neural Networks. ICASSP Kaidi Xu, Sijia Liu, Pin-Yu Chen, Mengshu Sun, Caiwen Ding, Bhavya Kailkhura, Xue Lin
2020	J	`jnl`	Towards an Efficient and General Framework of Robust Training for Graph Neural Networks. CoRR Kaidi Xu, Sijia Liu, Pin-Yu Chen, Mengshu Sun, Caiwen Ding, Bhavya Kailkhura, Xue Lin
2019	—	`conf`	A Majority Logic Synthesis Framework for Adiabatic Quantum-Flux-Parametron Superconducting Circuits. ACM Great Lakes Symposium on VLSI Ruizhe Cai, Olivia Chen, Ao Ren, Ning Liu, Caiwen Ding, Nobuyuki Yoshikawa, Yanzhi Wang
2019	J	`jnl`	A SOT-MRAM-based Processing-In-Memory Engine for Highly Compressed DNN Implementation. CoRR Geng Yuan, Xiaolong Ma, Sheng Lin, Zhengang Li, Caiwen Ding
2019	J	`jnl`	A Stochastic-Computing based Deep Learning Framework using Adiabatic Quantum-Flux-Parametron SuperconductingTechnology. CoRR Ruizhe Cai, Ao Ren, Olivia Chen, Ning Liu, Caiwen Ding, Xuehai Qian, Jie Han, Wenhui Luo, Nobuyuki Yoshikawa, Yanzhi Wang
2019	A*	`conf`	A stochastic-computing based deep learning framework using adiabatic quantum-flux-parametron superconducting technology. ISCA Ruizhe Cai, Ao Ren, Olivia Chen, Ning Liu, Caiwen Ding, Xuehai Qian, Jie Han, Wenhui Luo, Nobuyuki Yoshikawa, Yanzhi Wang
2019	A	`conf`	An Ultra-Efficient Memristor-Based DNN Framework with Structured Weight Pruning and Quantization Using ADMM. ISLPED Geng Yuan, Xiaolong Ma, Caiwen Ding, Sheng Lin, Tianyun Zhang, Zeinab S. Jalali, Yilong Zhao, Li Jiang, Sucheta Soundarajan, Yanzhi Wang
2019	J	`jnl`	An Ultra-Efficient Memristor-Based DNN Framework with Structured Weight Pruning and Quantization Using ADMM. CoRR Geng Yuan, Xiaolong Ma, Caiwen Ding, Sheng Lin, Tianyun Zhang, Zeinab S. Jalali, Yilong Zhao, Li Jiang, Sucheta Soundarajan, Yanzhi Wang
2019	—	`conf`	Deep Compressed Pneumonia Detection for Low-Power Embedded Devices. LABELS/HAL-MICCAI/CuRIOUS@MICCAI Hongjia Li, Sheng Lin, Ning Liu, Caiwen Ding, Yanzhi Wang
2019	J	`jnl`	Deep Compressed Pneumonia Detection for Low-Power Embedded Devices. CoRR Hongjia Li, Sheng Lin, Ning Liu, Caiwen Ding, Yanzhi Wang
2019	A*	`conf`	E-RNN: Design Optimization for Efficient Recurrent Neural Networks in FPGAs. HPCA Zhe Li, Caiwen Ding, Siyue Wang, Wujie Wen, Youwei Zhuo, Chang Liu, Qinru Qiu, Wenyao Xu, Xue Lin, Xuehai Qian, Yanzhi Wang
2019	J	`jnl`	HEIF: Highly Efficient Stochastic Computing-Based Inference Framework for Deep Neural Networks. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. Zhe Li, Ji Li, Ao Ren, Ruizhe Cai, Caiwen Ding, Xuehai Qian, Jeffrey Draper, Bo Yuan, Jian Tang, Qinru Qiu, Yanzhi Wang
2019	J	`jnl`	Normalization and dropout for stochastic computing-based deep convolutional neural networks. Integr. Ji Li, Zihao Yuan, Zhe Li, Ao Ren, Caiwen Ding, Jeffrey Draper, Shahin Nazarian, Qinru Qiu, Bo Yuan, Yanzhi Wang
2019	A	`conf`	REQ-YOLO: A Resource-Aware, Efficient Quantization Framework for Object Detection on FPGAs. FPGA Caiwen Ding, Shuo Wang, Ning Liu, Kaidi Xu, Yanzhi Wang, Yun Liang
2019	J	`jnl`	REQ-YOLO: A Resource-Aware, Efficient Quantization Framework for Object Detection on FPGAs. CoRR Caiwen Ding, Shuo Wang, Ning Liu, Kaidi Xu, Yanzhi Wang, Yun Liang
2019	J	`jnl`	Tiny but Accurate: A Pruned, Quantized and Optimized Memristor Crossbar Framework for Ultra Efficient DNN Implementation. CoRR Xiaolong Ma, Geng Yuan, Sheng Lin, Caiwen Ding, Fuxun Yu, Tao Liu, Wujie Wen, Xiang Chen, Yanzhi Wang
2018	—	`conf`	A Fast and Effective Memristor-Based Method for Finding Approximate Eigenvalues and Eigenvectors of Non-negative Matrices. ISVLSI Chenghong Wang, Zeinab S. Jalali, Caiwen Ding, Yanzhi Wang, Sucheta Soundarajan
2018	A	`conf`	C-LSTM: Enabling Efficient LSTM using Structured Compression Techniques on FPGAs. FPGA Shuo Wang, Zhe Li, Caiwen Ding, Bo Yuan, Qinru Qiu, Yanzhi Wang, Yun Liang
2018	J	`jnl`	C-LSTM: Enabling Efficient LSTM using Structured Compression Techniques on FPGAs. CoRR Shuo Wang, Zhe Li, Caiwen Ding, Bo Yuan, Yanzhi Wang, Qinru Qiu, Yun Liang
2018	J	`jnl`	Dynamic Reconfiguration of Thermoelectric Generators for Vehicle Radiators Energy Harvesting Under Location-Dependent Temperature Variations. IEEE Trans. Very Large Scale Integr. Syst. Jaemin Kim, Donkyu Baek, Caiwen Ding, Sheng Lin, Donghwa Shin, Xue Lin, Yanzhi Wang, Youngjin Cho, Sang Hyun Park, Naehyuck Chang
2018	J	`jnl`	E-RNN: Design Optimization for Efficient Recurrent Neural Networks in FPGAs. CoRR Zhe Li, Caiwen Ding, Siyue Wang, Wujie Wen, Youwei Zhuo, Chang Liu, Qinru Qiu, Wenyao Xu, Xue Lin, Xuehai Qian, Yanzhi Wang
2018	—	`conf`	Efficient Recurrent Neural Networks using Structured Matrices in FPGAs. ICLR (Workshop) Zhe Li, Shuo Wang, Caiwen Ding, Qinru Qiu, Yanzhi Wang, Yun Liang
2018	J	`jnl`	Efficient Recurrent Neural Networks using Structured Matrices in FPGAs. CoRR Zhe Li, Shuo Wang, Caiwen Ding, Qinru Qiu, Yanzhi Wang, Yun Liang
2018	A	`conf`	FFT-based deep learning deployment in embedded systems. DATE Sheng Lin, Ning Liu, Mahdi Nazemi, Hongjia Li, Caiwen Ding, Yanzhi Wang, Massoud Pedram
2018	B	`conf`	Learning Topics Using Semantic Locality. ICPR Ziyi Zhao, Krittaphat Pugdeethosapol, Sheng Lin, Zhe Li, Caiwen Ding, Yanzhi Wang, Qinru Qiu
2018	J	`jnl`	Learning Topics using Semantic Locality. CoRR Ziyi Zhao, Krittaphat Pugdeethosapol, Sheng Lin, Zhe Li, Caiwen Ding, Yanzhi Wang, Qinru Qiu
2018	J	`jnl`	Prediction-Based Fast Thermoelectric Generator Reconfiguration for Energy Harvesting from Vehicle Radiators. CoRR Hanchen Yang, Feiyang Kang, Caiwen Ding, Ji Li, Jaemin Kim, Donkyu Baek, Shahin Nazarian, Xue Lin, Paul Bogdan, Naehyuck Chang
2018	A	`conf`	Prediction-based fast thermoelectric generator reconfiguration for energy harvesting from vehicle radiators. DATE Hanchen Yang, Feiyang Kang, Caiwen Ding, Ji Li, Jaemin Kim, Donkyu Baek, Shahin Nazarian, Xue Lin, Paul Bogdan, Naehyuck Chang
2018	J	`jnl`	Reconfigurable Photovoltaic Systems for Electric Vehicles. IEEE Des. Test Caiwen Ding, Hongjia Li, Weiwei Zheng, Yanzhi Wang, Xue Lin
2018	—	`conf`	Structured Weight Matrices-Based Hardware Accelerators in Deep Neural Networks: FPGAs and ASICs. ACM Great Lakes Symposium on VLSI Caiwen Ding, Ao Ren, Geng Yuan, Xiaolong Ma, Jiayu Li, Ning Liu, Bo Yuan, Yanzhi Wang
2018	J	`jnl`	Structured Weight Matrices-Based Hardware Accelerators in Deep Neural Networks: FPGAs and ASICs. CoRR Caiwen Ding, Ao Ren, Geng Yuan, Xiaolong Ma, Jiayu Li, Ning Liu, Bo Yuan, Yanzhi Wang
2018	—	`conf`	Towards Budget-Driven Hardware Optimization for Deep Convolutional Neural Networks Using Stochastic Computing. ISVLSI Zhe Li, Ji Li, Ao Ren, Caiwen Ding, Jeffrey Draper, Qinru Qiu, Bo Yuan, Yanzhi Wang
2018	J	`jnl`	Towards Budget-Driven Hardware Optimization for Deep Convolutional Neural Networks using Stochastic Computing. CoRR Zhe Li, Ji Li, Ao Ren, Caiwen Ding, Jeffrey Draper, Qinru Qiu, Bo Yuan, Yanzhi Wang
2018	A*	`conf`	Towards Ultra-High Performance and Energy Efficiency of Deep Learning Systems: An Algorithm-Hardware Co-Optimization Framework. AAAI Yanzhi Wang, Caiwen Ding, Zhe Li, Geng Yuan, Siyu Liao, Xiaolong Ma, Bo Yuan, Xuehai Qian, Jian Tang, Qinru Qiu, Xue Lin
2018	J	`jnl`	Towards Ultra-High Performance and Energy Efficiency of Deep Learning Systems: An Algorithm-Hardware Co-Optimization Framework. CoRR Yanzhi Wang, Caiwen Ding, Zhe Li, Geng Yuan, Siyu Liao, Xiaolong Ma, Bo Yuan, Xuehai Qian, Jian Tang, Qinru Qiu, Xue Lin
2018	A*	`conf`	VIBNN: Hardware Acceleration of Bayesian Neural Networks. ASPLOS Ruizhe Cai, Ao Ren, Ning Liu, Caiwen Ding, Luhao Wang, Xuehai Qian, Massoud Pedram, Yanzhi Wang
2018	J	`jnl`	VIBNN: Hardware Acceleration of Bayesian Neural Networks. CoRR Ruizhe Cai, Ao Ren, Ning Liu, Caiwen Ding, Luhao Wang, Xuehai Qian, Massoud Pedram, Yanzhi Wang
2017	—	`conf`	Algorithm accelerations for luminescent solar concentrator-enhanced reconfigurable onboard photovoltaic system. ASP-DAC Caiwen Ding, Ji Li, Weiwei Zheng, Naehyuck Chang, Xue Lin, Yanzhi Wang
2017	J	`jnl`	CirCNN: Accelerating and Compressing Deep Neural Networks Using Block-CirculantWeight Matrices. CoRR Caiwen Ding, Siyu Liao, Yanzhi Wang, Zhe Li, Ning Liu, Youwei Zhuo, Chao Wang, Xuehai Qian, Yu Bai, Geng Yuan, Xiaolong Ma, Yipeng Zhang, Jian Tang, Qinru Qiu, Xue Lin, Bo Yuan
2017	A*	`conf`	CirCNN: accelerating and compressing deep neural networks using block-circulant weight matrices. MICRO Caiwen Ding, Siyu Liao, Yanzhi Wang, Zhe Li, Ning Liu, Youwei Zhuo, Chao Wang, Xuehai Qian, Yu Bai, Geng Yuan, Xiaolong Ma, Yipeng Zhang, Jian Tang, Qinru Qiu, Xue Lin, Bo Yuan
2017	J	`jnl`	FFT-Based Deep Learning Deployment in Embedded Systems. CoRR Sheng Lin, Ning Liu, Mahdi Nazemi, Hongjia Li, Caiwen Ding, Yanzhi Wang, Massoud Pedram
2017	J	`jnl`	Hardware-Driven Nonlinear Activation for Stochastic Computing Based Deep Convolutional Neural Networks. CoRR Ji Li, Zihao Yuan, Zhe Li, Caiwen Ding, Ao Ren, Qinru Qiu, Jeffrey T. Draper, Yanzhi Wang
2017	B	`conf`	Hardware-driven nonlinear activation for stochastic computing based deep convolutional neural networks. IJCNN Ji Li, Zihao Yuan, Zhe Li, Caiwen Ding, Ao Ren, Qinru Qiu, Jeffrey Draper, Yanzhi Wang
2017	—	`conf`	Memristor crossbar-based ultra-efficient next-generation baseband processors. MWSCAS Geng Yuan, Caiwen Ding, Ruizhe Cai, Xiaolong Ma, Ziyi Zhao, Ao Ren, Bo Yuan, Yanzhi Wang
2017	J	`jnl`	Multisource Indoor Energy Harvesting for Nonvolatile Processors. IEEE Des. Test Caiwen Ding, Ning Liu, Yanzhi Wang, Ji Li, Soroush Heidari, Jingtong Hu, Yongpan Liu
2017	A	`conf`	Reconfigurable thermoelectric generators for vehicle radiators energy harvesting. ISLPED Donkyu Baek, Caiwen Ding, Sheng Lin, Donghwa Shin, Jaemin Kim, Xue Lin, Yanzhi Wang, Naehyuck Chang
2017	A*	`conf`	SC-DCNN: Highly-Scalable Deep Convolutional Neural Network using Stochastic Computing. ASPLOS Ao Ren, Zhe Li, Caiwen Ding, Qinru Qiu, Yanzhi Wang, Ji Li, Xuehai Qian, Bo Yuan
2017	—	`conf`	Softmax Regression Design for Stochastic Computing Based Deep Convolutional Neural Networks. ACM Great Lakes Symposium on VLSI Zihao Yuan, Ji Li, Zhe Li, Caiwen Ding, Ao Ren, Bo Yuan, Qinru Qiu, Jeffrey Draper, Yanzhi Wang
2017	—	`conf`	Towards acceleration of deep convolutional neural networks using stochastic computing. ASP-DAC Ji Li, Ao Ren, Zhe Li, Caiwen Ding, Bo Yuan, Qinru Qiu, Yanzhi Wang
2016	C	`conf`	Dynamic converter reconfiguration for near-threshold non-volatile processors using in-door energy harvesting. ICCD Caiwen Ding, Hongjia Li, Jingtong Hu, Yongpan Liu, Yanzhi Wang
2016	C	`conf`	Luminescent solar concentrator-based photovoltaic reconfiguration for hybrid and plug-in electric vehicles. ICCD Caiwen Ding, Hongjia Li, Weiwei Zheng, Yanzhi Wang, Naehyuck Chang, Xue Lin
2016	C	`conf`	Multi-source in-door energy harvesting for non-volatile processors. ISCAS Caiwen Ding, Soroush Heidari, Yanzhi Wang, Yongpan Liu, Jingtong Hu
2016	—	`conf`	Neural Network-based Prediction Algorithms for In-Door Multi-Source Energy Harvesting System for Non-Volatile Processors. ACM Great Lakes Symposium on VLSI Ning Liu, Caiwen Ding, Yanzhi Wang, Jingtong Hu
2016	J	`jnl`	SC-DCNN: Highly-Scalable Deep Convolutional Neural Network using Stochastic Computing. CoRR Ao Ren, Ji Li, Zhe Li, Caiwen Ding, Xuehai Qian, Qinru Qiu, Bo Yuan, Yanzhi Wang
2015	—	`conf`	Multi-source energy harvesting management and optimization for non-volatile processors. IGSC Soroush Heidari, Caiwen Ding, Yongpan Liu, Yanzhi Wang, Jingtong Hu