A Nonlinear Decoupling Control Approach Using RBFNNI-Based Robust Pole Placement for a Permanent Magnet In-Wheel Motor. - Yong Li 020; Bin Li; Xing Xu 002; Xiaodong Sun 001 (IEEE Access, 2018)

GA-BPNN Based Hybrid Steering Control Approach for Unmanned Driving Electric Vehicle with In-Wheel Motors. - Yong Li 020; Xing Xu 002; Wujie Wang (Complex., 2018)

AliGraph: A Comprehensive Graph Neural Network Platform. - Rong Zhu; Kun Zhao; Hongxia Yang; Wei Lin 016; Chang Zhou; Baole Ai; Yong Li 020; Jingren Zhou 001 (Proc. VLDB Endow., 2019)

AntMan: Dynamic Scaling on GPU Clusters for Deep Learning. - Wencong Xiao; Shiru Ren; Yong Li 020; Yang Zhang; Pengyang Hou; Zhi Li; Yihui Feng; Wei Lin 016; Yangqing Jia (OSDI, 2020)

MicroRec: Accelerating Deep Recommendation Systems to Microseconds by Hardware and Data Structure Solutions. - Wenqi Jiang 001; Zhenhao He; Shuai Zhang 007; Thomas B. Preußer; Kai Zeng 002; Liang Feng; Jiansong Zhang 001; Tongxuan Liu; Yong Li 020; Jingren Zhou 001; Ce Zhang 001; Gustavo Alonso (CoRR, 2020)

Whale: A Unified Distributed Training Framework. - Ang Wang; Xianyan Jia; Le Jiang; Jie Zhang 078; Yong Li 020; Wei Lin 016 (CoRR, 2020)

EasyTransfer - A Simple and Scalable Deep Transfer Learning Platform for NLP Applications. - Minghui Qiu; Peng Li 056; Hanjie Pan; Chengyu Wang 001; Ang Wang; Cen Chen 001; Yaliang Li; Dehong Gao; Jun Huang 007; Yong Li 020; Jun Yang 052; Deng Cai 001; et al. (CoRR, 2020)

Focusing More on Conflicts with Mis-Predictions Helps Language Pre-Training. - Chen Xing; Wencong Xiao; Yong Li 020; Wei Lin 016 (CoRR, 2020)

FleetRec: Large-Scale Recommendation Inference on Hybrid GPU-FPGA Clusters. - Wenqi Jiang 001; Zhenhao He; Shuai Zhang 007; Kai Zeng 002; Liang Feng; Jiansong Zhang 001; Tongxuan Liu; Yong Li 020; Jingren Zhou 001; Ce Zhang 001; Gustavo Alonso (KDD, 2021)

MicroRec: Efficient Recommendation Inference by Hardware and Data Structure Solutions. - Wenqi Jiang 001; Zhenhao He; Shuai Zhang 007; Thomas B. Preußer; Kai Zeng 002; Liang Feng; Jiansong Zhang 001; Tongxuan Liu; Yong Li 020; Jingren Zhou 001; Ce Zhang 001; Gustavo Alonso (MLSys, 2021)

M6: A Chinese Multimodal Pretrainer. - Junyang Lin; Rui Men; An Yang; Chang Zhou; Ming Ding 004; Yichang Zhang; Peng Wang 028; Ang Wang; Le Jiang; Xianyan Jia; Jie Zhang 078; Jianwei Zhang 012; et al. (CoRR, 2021)

Exploring Sparse Expert Models and Beyond. - An Yang; Junyang Lin; Rui Men; Chang Zhou; Le Jiang; Xianyan Jia; Ang Wang; Jie Zhang 078; Jiamang Wang; Yong Li 020; Di Zhang; Wei Lin 016; et al. (CoRR, 2021)

M6-10T: A Sharing-Delinking Paradigm for Efficient Multi-Trillion Parameter Pretraining. - Junyang Lin; An Yang; Jinze Bai; Chang Zhou; Le Jiang; Xianyan Jia; Ang Wang; Jie Zhang 078; Yong Li 020; Wei Lin 016; Jingren Zhou 001; Hongxia Yang (CoRR, 2021)

GraphScope: A Unified Engine For Big Graph Processing. - Wenfei Fan; Tao He; Longbin Lai; Xue Li 024; Yong Li 020; Zhao Li 007; Zhengping Qian; Chao Tian 001; Lei Wang 004; Jingbo Xu 001; Youyang Yao; Qiang Yin 002; et al. (Proc. VLDB Endow., 2021)

Revisiting and Advancing Chinese Natural Language Understanding with Accelerated Heterogeneous Knowledge Pre-training. - Taolin Zhang 001; Junwei Dong; Jianing Wang 002; Chengyu Wang 001; Ang Wang; Yinghui Liu; Jun Huang 007; Yong Li 020; Xiaofeng He (EMNLP (Industry Track), 2022)

PICASSO: Unleashing the Potential of GPU-centric Training for Wide-and-deep Recommender Systems. - Yuanxing Zhang; Langshi Chen; Siran Yang; Man Yuan; Huimin Yi; Jie Zhang 078; Jiamang Wang; Jianbo Dong; Yunlong Xu; Yue Song; Yong Li 020; Di Zhang; et al. (ICDE, 2022)

MLaaS in the Wild: Workload Analysis and Scheduling in Large-Scale Heterogeneous GPU Clusters. - Qizhen Weng; Wencong Xiao; Yinghao Yu; Wei Wang 030; Cheng Wang; Jian He; Yong Li 020; Liping Zhang; Wei Lin 016; Yu Ding (NSDI, 2022)

CoGNN: Efficient Scheduling for Concurrent GNN Training on GPUs. - Qingxiao Sun; Yi Liu 013; Hailong Yang 002; Ruizhe Zhang 012; Ming Dun; Mingzhen Li 001; Xiaoyan Liu; Wencong Xiao; Yong Li 020; Zhongzhi Luan; Depei Qian (SC, 2022)

Whale: Efficient Giant Model Training over Heterogeneous GPUs. - Xianyan Jia; Le Jiang; Ang Wang; Wencong Xiao; Ziji Shi; Jie Zhang 078; Xinyuan Li; Langshi Chen; Yong Li 020; Zhen Zheng; Xiaoyong Liu; Wei Lin 016 (USENIX ATC, 2022)

EasyScale: Accuracy-consistent Elastic Training for Deep Learning. - Mingzhen Li 001; Wencong Xiao; Biao Sun; Hanyu Zhao; Hailong Yang 002; Shiru Ren; Zhongzhi Luan; Xianyan Jia; Yi Liu 013; Yong Li 020; Depei Qian; Wei Lin 016 (CoRR, 2022)

uGrapher: High-Performance Graph Operator Computation via Unified Abstraction for Graph Neural Networks. - Yangjie Zhou 001; Jingwen Leng; Yaoxu Song; Shuwen Lu; Mian Wang; Chao Li 009; Minyi Guo; Wenting Shen; Yong Li 020; Wei Lin 016; Xiangwen Liu; Hanqing Wu (ASPLOS (2), 2023)

EasyScale: Elastic Training with Consistent Accuracy and Improved Utilization on GPUs. - Mingzhen Li 001; Wencong Xiao; Hailong Yang 002; Biao Sun; Hanyu Zhao; Shiru Ren; Zhongzhi Luan; Xianyan Jia; Yi Liu 013; Yong Li 020; Wei Lin 016; Depei Qian (SC, 2023)

Legion: Automatically Pushing the Envelope of Multi-GPU System for Billion-Scale GNN Training. - Jie Sun 017; Li Su 005; Zuocheng Shi; Wenting Shen; Zeke Wang; Lei Wang 004; Jie Zhang 081; Yong Li 020; Wenyuan Yu; Jingren Zhou 001; Fei Wu 001 (USENIX ATC, 2023)

TAP: Accelerating Large-Scale DNN Training Through Tensor Automatic Parallelisation. - Ziji Shi; Le Jiang; Ang Wang; Jie Zhang 078; Xianyan Jia; Yong Li 020; Chencan Wu; Jialin Li; Wei Lin 016 (CoRR, 2023)

Flash-LLM: Enabling Cost-Effective and Highly-Efficient Large Generative Model Inference with Unstructured Sparsity. - Haojun Xia; Zhen Zheng; Yuchao Li; Donglin Zhuang; Zhongzhu Zhou; Xiafei Qiu; Yong Li 020; Wei Lin 016; Shuaiwen Leon Song (CoRR, 2023)

GoldMiner: Elastic Scaling of Training Data Pre-Processing Pipelines for Deep Learning. - Hanyu Zhao; Zhi Yang 001; Yu Cheng; Chao Tian 001; Shiru Ren; Wencong Xiao; Man Yuan; Langshi Chen; Kaibo Liu; Yang Zhang; Yong Li 020; Wei Lin 016 (Proc. ACM Manag. Data, 2023)

Flash-LLM: Enabling Low-Cost and Highly-Efficient Large Generative Model Inference With Unstructured Sparsity. - Haojun Xia; Zhen Zheng; Yuchao Li; Donglin Zhuang; Zhongzhu Zhou; Xiafei Qiu; Yong Li 020; Wei Lin 016; Shuaiwen Leon Song (Proc. VLDB Endow., 2023)

Llumnix: Dynamic Scheduling for Large Language Model Serving. - Biao Sun; Ziming Huang; Hanyu Zhao; Wencong Xiao; Xinyi Zhang; Yong Li 020; Wei Lin 016 (OSDI, 2024)

Infinite-LLM: Efficient LLM Service for Long Context with DistAttention and Distributed KVCache. - Bin Lin; Tao Peng; Chen Zhang; Minmin Sun; Lanbo Li; Hanyu Zhao; Wencong Xiao; Qi Xu; Xiafei Qiu; Shen Li; Zhigang Ji; Yong Li 020; et al. (CoRR, 2024)

Rubick: Exploiting Job Reconfigurability for Deep Learning Cluster Scheduling. - Xinyi Zhang; Hanyu Zhao; Wencong Xiao; Xianyan Jia; Fei Xu; Yong Li 020; Wei Lin 016; Fangming Liu (CoRR, 2024)

ElasticBatch: A Learning-Augmented Elastic Scheduling System for Batch Inference on MIG. - Jiaxing Qi; Wencong Xiao; Mingzhen Li 001; Chaojie Yang; Yong Li 020; Wei Lin 016; Hailong Yang 002; Zhongzhi Luan; Depei Qian (IEEE Trans. Parallel Distributed Syst., 2024)

Helios: Efficient Distributed Dynamic Graph Sampling for Online GNN Inference. - Jie Sun 017; Zuocheng Shi; Li Su 005; Wenting Shen; Zeke Wang; Yong Li 020; Wenyuan Yu; Wei Lin 016; Fei Wu 001; Bingsheng He; Jingren Zhou 001 (PPoPP, 2025)

Qwen2.5-1M Technical Report. - An Yang; Bowen Yu 002; Chengyuan Li; Dayiheng Liu; Fei Huang 005; Haoyan Huang; Jiandong Jiang; Jianhong Tu; Jianwei Zhang 012; Jingren Zhou 001; Junyang Lin; Kai Dang; et al. (CoRR, 2025)

Efficient Long Context Fine-tuning with Chunk Flow. - Xiulong Yuan; Hongtao Xu; Wenting Shen; Ang Wang; Xiafei Qiu; Jie Zhang 078; Yuqiong Liu; Bowen Yu 002; Junyang Lin; Mingzhen Li 001; Weile Jia; Yong Li 020; et al. (CoRR, 2025)