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ORCIDQizhen Weng 0001
Person information
- affiliation: China Telecom, Institute of Artificial Intelligence (TeleAI), China
- affiliation: Shanghai AI Laboratory, China
- affiliation (PhD 2022): Hong Kong University of Science and Technology, Hong Kong
Other persons with the same name
- Qizhen Weng — disambiguation page
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2020 – today
- 2026
[i7]Weiye Wang, Chen Chen, Junxue Zhang, Zhusheng Wang, Hui Yuan, Zixuan Guan, Xiaolong Zheng, Qizhen Weng, Yin Chen, Minyi Guo:
CALVO: Improve Serving Efficiency for LLM Inferences with Intense Network Demands. CoRR abs/2603.21257 (2026)- 2025
- [c10]Lingyun Yang, Yongchen Wang, Yinghao Yu, Qizhen Weng, Jianbo Dong, Kan Liu, Chi Zhang, Yanyi Zi, Hao Li, Zechao Zhang, Nan Wang, Yu Dong, Menglei Zheng, Lanlan Xi, Xiaowei Lu, Liang Ye, Guodong Yang, Binzhang Fu, Tao Lan, Liping Zhang, Lin Qu, Wei Wang:
GPU-Disaggregated Serving for Deep Learning Recommendation Models at Scale. NSDI 2025: 847-863 - [c9]Suyi Li, Hanfeng Lu, Tianyuan Wu, Minchen Yu, Qizhen Weng, Xusheng Chen, Yizhou Shan, Binhang Yuan, Wei Wang:
Toppings: CPU-Assisted, Rank-Aware Adapter Serving for LLM Inference. USENIX ATC 2025: 613-629 - [i6]Tianze Wang, Yifei Liu, Chen Chen, Pengfei Zuo, Jiawei Zhang, Qizhen Weng, Yin Chen, Zhenhua Han, Jieru Zhao, Quan Chen, Minyi Guo:
Efficient Unified Caching for Accelerating Heterogeneous AI Workloads. CoRR abs/2506.12370 (2025) - [i5]Zhexiang Zhang, Ye Wang, Xiangyu Wang, Yumiao Zhao, Jingzhe Jiang, Qizhen Weng, Shaohuai Shi, Yin Chen, Minchen Yu:
Janus: Disaggregating Attention and Experts for Scalable MoE Inference. CoRR abs/2512.13525 (2025) - 2024
- [i4]Suyi Li, Hanfeng Lu, Tianyuan Wu, Minchen Yu, Qizhen Weng
, Xusheng Chen, Yizhou Shan, Binhang Yuan, Wei Wang:
CaraServe: CPU-Assisted and Rank-Aware LoRA Serving for Generative LLM Inference. CoRR abs/2401.11240 (2024) - [i3]Zheng Cai, Maosong Cao, Haojiong Chen, Kai Chen, Keyu Chen, Xin Chen, Xun Chen, Zehui Chen, Zhi Chen, Pei Chu, Xiaoyi Dong, Haodong Duan, Qi Fan, Zhaoye Fei, Yang Gao, Jiaye Ge, Chenya Gu, Yuzhe Gu, Tao Gui, Aijia Guo, Qipeng Guo, Conghui He, Yingfan Hu, Ting Huang, Tao Jiang, Penglong Jiao, Zhenjiang Jin, Zhikai Lei, Jiaxing Li, Jingwen Li, Linyang Li, Shuaibin Li, Wei Li, Yining Li, Hongwei Liu, Jiangning Liu, Jiawei Hong, Kaiwen Liu, Kuikun Liu, Xiaoran Liu, Chengqi Lv, Haijun Lv, Kai Lv, Li Ma, Runyuan Ma, Zerun Ma, Wenchang Ning, Linke Ouyang, Jiantao Qiu, Yuan Qu, Fukai Shang, Yunfan Shao, Demin Song, Zifan Song, Zhihao Sui, Peng Sun, Yu Sun, Huanze Tang, Bin Wang, Guoteng Wang, Jiaqi Wang, Jiayu Wang, Rui Wang, Yudong Wang, Ziyi Wang, Xingjian Wei, Qizhen Weng, Fan Wu, Yingtong Xiong, Xiaomeng Zhao, et al.:
InternLM2 Technical Report. CoRR abs/2403.17297 (2024) - [i2]Jiangfei Duan, Shuo Zhang, Zerui Wang, Lijuan Jiang, Wenwen Qu, Qinghao Hu, Guoteng Wang, Qizhen Weng, Hang Yan, Xingcheng Zhang, Xipeng Qiu, Dahua Lin, Yonggang Wen, Xin Jin, Tianwei Zhang, Peng Sun:
Efficient Training of Large Language Models on Distributed Infrastructures: A Survey. CoRR abs/2407.20018 (2024) - 2023
- [j1]Chen Chen, Qizhen Weng, Wei Wang, Baochun Li, Bo Li:
Accelerating Distributed Learning in Non-Dedicated Environments. IEEE Trans. Cloud Comput. 11(1): 515-531 (2023) - [c8]Qizhen Weng, Lingyun Yang, Yinghao Yu, Wei Wang, Xiaochuan Tang, Guodong Yang, Liping Zhang:
Beware of Fragmentation: Scheduling GPU-Sharing Workloads with Fragmentation Gradient Descent. USENIX ATC 2023: 995-1008 - 2022
- [c7]Yongkang Zhang, Yinghao Yu, Wei Wang, Qiukai Chen, Jie Wu, Zuowei Zhang, Jiang Zhong, Tianchen Ding, Qizhen Weng, Lingyun Yang, Cheng Wang, Jian He, Guodong Yang, Liping Zhang:
Workload consolidation in alibaba clusters: the good, the bad, and the ugly. SoCC 2022: 210-225 - [c6]Qizhen Weng, Wencong Xiao, Yinghao Yu, Wei Wang, Cheng Wang, Jian He, Yong Li, Liping Zhang, Wei Lin, Yu Ding:
MLaaS in the Wild: Workload Analysis and Scheduling in Large-Scale Heterogeneous GPU Clusters. NSDI 2022: 945-960 - 2020
- [c5]Chen Chen, Qizhen Weng, Wei Wang, Baochun Li, Bo Li:
Semi-dynamic load balancing: efficient distributed learning in non-dedicated environments. SoCC 2020: 431-446 - [c4]Luping Wang, Qizhen Weng, Wei Wang, Chen Chen, Bo Li:
Metis: learning to schedule long-running applications in shared container clusters at scale. SC 2020: 68
2010 – 2019
- 2019
- [c3]Huangshi Tian, Qizhen Weng, Wei Wang:
Towards Framework-Independent, Non-Intrusive Performance Characterization for Dataflow Computation. APSys 2019: 54-60 - 2018
- [c2]Chen Chen, Qizhen Weng, Wei Wang, Baochun Li, Bo Li:
Fast Distributed Deep Learning via Worker-adaptive Batch Sizing. SoCC 2018: 521 - [c1]Yinghao Yu, Wei Wang, Jun Zhang, Qizhen Weng, Khaled Ben Letaief:
OpuS: Fair and Efficient Cache Sharing for In-Memory Data Analytics. ICDCS 2018: 154-164 - [i1]Chen Chen, Qizhen Weng, Wei Wang, Baochun Li, Bo Li:
Fast Distributed Deep Learning via Worker-adaptive Batch Sizing. CoRR abs/1806.02508 (2018)
Coauthor Index
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