Accelerating CNN Training by Sparsifying Activation Gradients. - Xucheng Ye; Jianlei Yang 001; Pengcheng Dai; Yiran Chen 001; Weisheng Zhao (CoRR, 2019)

SparseTrain: Exploiting Dataflow Sparsity for Efficient Convolutional Neural Networks Training. - Pengcheng Dai; Jianlei Yang 001; Xucheng Ye; Xingzhou Cheng; Junyu Luo 002; Linghao Song; Yiran Chen 001; Weisheng Zhao (DAC, 2020)

Accelerating CNN Training by Pruning Activation Gradients. - Xucheng Ye; Pengcheng Dai; Junyu Luo 002; Xin Guo 008; Yingjie Qi; Jianlei Yang 001; Yiran Chen 001 (ECCV (25), 2020)

FedSkel: Efficient Federated Learning on Heterogeneous Systems with Skeleton Gradients Update. - Junyu Luo 002; Jianlei Yang 001; Xucheng Ye; Xin Guo 008; Weisheng Zhao (CIKM, 2021)

RoSearch: Search for Robust Student Architectures When Distilling Pre-trained Language Models. - Xin Guo 008; Jianlei Yang 001; Haoyi Zhou; Xucheng Ye; Jianxin Li 002 (CoRR, 2021)

S2Engine: A Novel Systolic Architecture for Sparse Convolutional Neural Networks. - Jianlei Yang 001; Wenzhi Fu; Xingzhou Cheng; Xucheng Ye; Pengcheng Dai; Weisheng Zhao (CoRR, 2021)

S2 Engine: A Novel Systolic Architecture for Sparse Convolutional Neural Networks. - Jianlei Yang 001; Wenzhi Fu; Xingzhou Cheng; Xucheng Ye; Pengcheng Dai; Weisheng Zhao (IEEE Trans. Computers, 2022)

KwaiYiiMath: Technical Report. - Jia-Yi Fu; Lei Lin; Xiaoyang Gao; Pengli Liu; Zhengzong Chen; Zhirui Yang; Shengnan Zhang; Xue Zheng; Yan Li 043; Yuliang Liu; Xucheng Ye; Yiqiao Liao; et al. (CoRR, 2023)

NAND-SPIN-based processing-in-MRAM architecture for convolutional neural network acceleration. - Yinglin Zhao; Jianlei Yang 001; Bing Li; Xingzhou Cheng; Xucheng Ye; Xueyan Wang; Xiaotao Jia; Zhaohao Wang; Youguang Zhang; Weisheng Zhao (Sci. China Inf. Sci., 2023)

DSMPC-DCBF: A Hierarchical Parking Trajectory Optimization Method Based on MPC. - Siqi Duan; Wenwei Wang; Xucheng Ye; Jinrui Nan; Jingyuan Zhao; Andrew F. Burke (ACIRS, 2024)

Accelerating the Training of Large Language Models using Efficient Activation Rematerialization and Optimal Hybrid Parallelism. - Tailing Yuan; Yuliang Liu; Xucheng Ye; Shenglong Zhang; Jianchao Tan; Bin Chen; Chengru Song; Di Zhang (USENIX ATC, 2024)

Towards Comprehensive Preference Data Collection for Reward Modeling. - Yulan Hu; Qingyang Li 001; Sheng Ouyang; Ge Chen 006; Kaihui Chen; Lijun Mei; Xucheng Ye; Fuzheng Zhang; Yong Liu 018 (CoRR, 2024)