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Jiamang Wang
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2020 – today
- 2024
- [c3]Xiaoyang Zhao
, Siran Yang
FaPES: Enabling Efficient Elastic Scaling for Serverless Machine Learning Platforms. SoCC 2024: 443-459 - [i9]Haoran Que, Jiaheng Liu, Ge Zhang, Chenchen Zhang, Xingwei Qu, Yinghao Ma, Feiyu Duan, Zhiqi Bai, Jiakai Wang, Yuanxing Zhang, Xu Tan, Jie Fu, Wenbo Su, Jiamang Wang, Lin Qu, Bo Zheng:
D-CPT Law: Domain-specific Continual Pre-Training Scaling Law for Large Language Models. CoRR abs/2406.01375 (2024) - [i8]Jianbo Dong, Bin Luo, Jun Zhang, Pengcheng Zhang, Fei Feng, Yikai Zhu, Ang Liu, Zian Chen, Yi Shi, Hairong Jiao, Gang Lu, Yu Guan, Ennan Zhai, Wencong Xiao, Hanyu Zhao, Man Yuan, Siran Yang, Xiang Li, Jiamang Wang, Rui Men, Jianwei Zhang, Huang Zhong, Dennis Cai, Yuan Xie, Binzhang Fu:
Boosting Large-scale Parallel Training Efficiency with C4: A Communication-Driven Approach. CoRR abs/2406.04594 (2024) - [i7]Jiaheng Liu, Chenchen Zhang, Jinyang Guo, Yuanxing Zhang, Haoran Que, Ken Deng, Zhiqi Bai, Jie Liu, Ge Zhang, Jiakai Wang, Yanan Wu, Congnan Liu, Wenbo Su, Jiamang Wang, Lin Qu, Bo Zheng:
DDK: Distilling Domain Knowledge for Efficient Large Language Models. CoRR abs/2407.16154 (2024) - [i6]Tianyuan Wu, Wei Wang, Yinghao Yu, Siran Yang, Wenchao Wu, Qinkai Duan, Guodong Yang, Jiamang Wang, Lin Qu, Liping Zhang:
FALCON: Pinpointing and Mitigating Stragglers for Large-Scale Hybrid-Parallel Training. CoRR abs/2410.12588 (2024) - [i5]Yanshi Li, Shaopan Xiong, Gengru Chen, Xiaoyang Li, Yijia Luo, Xingyao Zhang, Yanhui Huang, Xingyuan Bu, Yingshui Tan, Chun Yuan, Jiamang Wang, Wenbo Su, Bo Zheng:
Adaptive Dense Reward: Understanding the Gap Between Action and Reward Space in Alignment. CoRR abs/2411.00809 (2024) - 2023
- [i4]Siyu Wang, Zongyan Cao, Chang Si, Lansong Diao, Jiamang Wang, Wei Lin:
Ada-Grouper: Accelerating Pipeline Parallelism in Preempted Network by Adaptive Group-Scheduling for Micro-Batches. CoRR abs/2303.01675 (2023) - 2022
- [c2]Yuanxing Zhang, Langshi Chen, Siran Yang, Man Yuan
PICASSO: Unleashing the Potential of GPU-centric Training for Wide-and-deep Recommender Systems. ICDE 2022: 3453-3466 - [i3]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:
PICASSO: Unleashing the Potential of GPU-centric Training for Wide-and-deep Recommender Systems. CoRR abs/2204.04903 (2022) - 2021
- [j1]Yingda Chen, Jiamang Wang, Yifeng Lu, Ying Han, Zhiqiang Lv, Xuebin Min, Hua Cai, Wei Zhang, Haochuan Fan, Chao Li, Tao Guan, Wei Lin, Yangqing Jia, Jingren Zhou:
Fangorn: Adaptive Execution Framework for Heterogeneous Workloads on Shared Clusters. Proc. VLDB Endow. 14(12): 2972-2985 (2021) - [c1]Chenyi Lei, Shixian Luo, Yong Liu
Understanding Chinese Video and Language via Contrastive Multimodal Pre-Training. ACM Multimedia 2021: 2567-2576 - [i2]Chenyi Lei, Shixian Luo, Yong Liu, Wanggui He, Jiamang Wang, Guoxin Wang, Haihong Tang, Chunyan Miao, Houqiang Li:
Understanding Chinese Video and Language via Contrastive Multimodal Pre-Training. CoRR abs/2104.09411 (2021) - [i1]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:
Exploring Sparse Expert Models and Beyond. CoRR abs/2105.15082 (2021)
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