Jie Zhang

According to our database, Jie Zhang authored at least 11 papers between 2020 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Contextual Generative Auction with Permutation-level Externalities for Online Advertising.

Ruitao Zhu, Yangsu Liu, Dagui Chen, Zhenjia Ma, Chufeng Shi, Zhenzhe Zheng, Jie Zhang, Jian Xu, Bo Zheng, Fan Wu

Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, V.1, 2025

Efficient Long Context Fine-tuning with Chunk Flow.

Xiulong Yuan, Hongtao Xu, Wenting Shen, Ang Wang, Xiafei Qiu, Jie Zhang, Yuqiong Liu, Bowen Yu, Junyang Lin, Mingzhen Li, Weile Jia, Yong Li, Wei Lin

Proceedings of the Forty-second International Conference on Machine Learning, 2025

Spindle: Efficient Distributed Training of Multi-Task Large Models via Wavefront Scheduling.

Yujie Wang, Shenhan Zhu, Fangcheng Fu, Xupeng Miao, Jie Zhang, Juan Zhu, Fan Hong, Yong Li, Bin Cui

Proceedings of the 30th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, 2025

2024

BladeDISC++: Memory Optimizations Based On Symbolic Shape.

Xiulong Yuan, Xu Yan, Wenting Shen, Xiafei Qiu, Ang Wang, Jie Zhang, Yong Li, Wei Lin

CoRR, 2024

2023

TAP: Accelerating Large-Scale DNN Training Through Tensor Automatic Parallelisation.

Ziji Shi, Le Jiang, Ang Wang, Jie Zhang, Xianyan Jia, Yong Li, Chencan Wu, Jialin Li, Wei Lin

CoRR, 2023

2022

Whale: Efficient Giant Model Training over Heterogeneous GPUs.

Xianyan Jia, Le Jiang, Ang Wang, Wencong Xiao, Ziji Shi, Jie Zhang, Xinyuan Li, Langshi Chen, Yong Li, Zhen Zheng, Xiaoyong Liu, Wei Lin

Proceedings of the 2022 USENIX Annual Technical Conference, 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, Jiamang Wang, Jianbo Dong, Yunlong Xu, Yue Song, Yong Li, Di Zhang, Wei Lin, Lin Qu, Bo Zheng

Proceedings of the 38th IEEE International Conference on Data Engineering, 2022

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, Yong Li, Wei Lin, Jingren Zhou, Hongxia Yang

CoRR, 2021

Exploring Sparse Expert Models and Beyond.

An Yang, Junyang Lin, Rui Men, Chang Zhou, Le Jiang, Xianyan Jia, Ang Wang, Jie Zhang, Jiamang Wang, Yong Li, Di Zhang, Wei Lin, Lin Qu, Jingren Zhou, Hongxia Yang

CoRR, 2021

M6: A Chinese Multimodal Pretrainer.

Junyang Lin, Rui Men, An Yang, Chang Zhou, Ming Ding, Yichang Zhang, Peng Wang, Ang Wang, Le Jiang, Xianyan Jia, Jie Zhang, Jianwei Zhang, Xu Zou, Zhikang Li, Xiaodong Deng, Jie Liu, Jinbao Xue, Huiling Zhou, Jianxin Ma, Jin Yu, Yong Li, Wei Lin, Jingren Zhou, Jie Tang, Hongxia Yang

CoRR, 2021

2020

Whale: A Unified Distributed Training Framework.

Ang Wang, Xianyan Jia, Le Jiang, Jie Zhang, Yong Li, Wei Lin

CoRR, 2020