Publications
* indicates equal contribution, # indicates corresponding author
2025
- Malleus: Straggler-Resilient Hybrid Parallel Training of Large-scale Models via Malleable Data and Model Parallelization
Haoyang Li*, Fangcheng Fu*#, Hao Ge, Sheng Lin, Xuanyu Wang, Jiawen Niu, Yujie Wang, Hailin Zhang, Xiaonan Nie, Bin Cui#
SIGMOD 2025 - PQCache: Product Quantization-based KVCache for Long Context LLM Inference
Hailin Zhang, Xiaodong Ji, Yilin Chen, Fangcheng Fu, Xupeng Miao, Xiaonan Nie, Weipeng Chen, Bin Cui
SIGMOD 2025 - Memo: Fine-grained Tensor Management For Ultra-long Context LLM Training
Pinxue Zhao, Hailin Zhang, Fangcheng Fu#, Xiaonan Nie, Qibin Liu, Fang Yang, Yuanbo Peng, Dian Jiao, Shuaipeng Li, Jinbao Xue, Yangyu Tao, Bin Cui#
SIGMOD 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#
ASPLOS 2025 - FlexSP: Accelerating Large Language Model Training via Flexible Sequence Parallelism
Yujie Wang, Shiju Wang, Shenhan Zhu, Fangcheng Fu#, Xinyi Liu, Xuefeng Xiao, Huixia Li, Jiashi Li, Faming Wu, Bin Cui#
ASPLOS 2025 - NetMoE: Accelerating MoE Training through Dynamic Sample Placement
Xinyi Liu, Yujie Wang, Fangcheng Fu, Xupeng Miao, Shenhan Zhu, Xiaonan Nie, Bin Cui
ICLR 2025 (Spotlight) - ThunderServe: High-performance and Cost-efficient LLM Serving in Cloud Environments
Youhe Jiang*, Fangcheng Fu*, Xiaozhe Yao*, Taiyi Wang, Bin Cui, Ana Klimovic, Eiko Yoneki
MLSys 2025 - Towards Scalable and Efficient Graph Structure Learning
Siqi Shen, Wentao Zhang, Chengshuo Du, Chong Chen, Fangcheng Fu, Yingxia, Shao, Bin Cui
ICDE 2025 - Hounding Data Diversity: Towards Participant Selection in Vertical Federated Learning
Xiaokai Zhou, Xiao Yan, Fangcheng Fu, Xinyan Li, Hao Huang, Quanqing Xu, Chuanhui Yang, Bo Du, Tieyun Qian, Jiawei Jiang
ICDE 2025 - Detecting and Analyzing Motifs in Large-scale Online Transaction Networks
Jiawei Jiang, Hao Huang, Zhigao Zheng, Yi Wei, Fangcheng Fu, Xiaosen Li, Bin Cui
TKDE 37(2): 584-596 (2025) - HaCore: Efficient Coreset Construction with Locality Sensitive Hashing for Vertical Federated Learning
Qinbo Zhang, Xiao Yan, Yukai Ding, Fangcheng Fu, Quanqing Xu, Ziyi Li, Chuang Hu, Jiawei Jiang
AAAI 2025 - RAP: Random Projection is What You Need for Vertical Federated Learning
Qinbo Zhang, Xiao Yan, Yukai Ding,Fangcheng Fu, Chuang Hu, Quanqing Xu, Xu Chen, Jiawei Jiang
DASFFA 2025
2024
- Enabling Parallelism Hot Switching for Efficient Training of Large Language Models
Hao Ge*, Fangcheng Fu*#, Haoyang Li, Xuanyu Wang, Sheng Lin, Yujie Wang, Xiaonan Nie, Hailin Zhang, Xupeng Miao, Bin Cui#
SOSP 2024 - Efficient Multi-task LLM Quantization and Serving for Multiple LoRA Adapters
Yifei Xia, Fangcheng Fu#, Wentao Zhang, Jiawei Jiang, Bin Cui#
NeurIPS 2024 - LSH-MoE: Communication-efficient MoE Training via Locality-Sensitive Hashing
Xiaonan Nie, Qibin Liu, Fangcheng Fu#, Shenhan Zhu, Xupeng Miao, Xiaoyang Li, Yang Zhang, Shouda Liu, Bin Cui#
NeurIPS 2024 - ProjPert: Projection-based Perturbation for Label Protection in Split Learning based Vertical Federated Learning
Fangcheng Fu, Xuanyu Wang, Jiawei Jiang, Huanran Xue, and Bin Cui
TKDE 36(7): 3417-3428 (2024) - Improving Automatic Parallel Training via Balanced Memory Workload Optimization
Yujie Wang, Youhe Jiang, Xupeng Miao#, Fangcheng Fu#, Shenhan Zhu, Xiaonan Nie, Yaofeng Tu, Bin Cui#
TKDE 36(8): 3906-3920 (2024) - Accelerating Text-to-image Editing via Cache-enabled Sparse Diffusion Inference
Zihao Yu, Haoyang Li, Fangcheng Fu, Xupeng Miao, Bin Cui
AAAI 2024 - X-former Elucidator: Reviving Efficient Attention for Long Context Language Modeling
Xupeng Miao, Shenhan Zhu, Fangcheng Fu, Ziyu Guo, Zhi Yang, Yaofeng Tu, Zhihao Jia, Bin Cui
IJCAI 2024 - Generative and Contrastive Paradigms Are Complementary for Graph Self-Supervised Learning
Yuxiang Wang, Xiao Yan, Chuang Hu, Quanqing Xu, Chuanhui Yang, Fangcheng Fu, Wentao Zhang, Hao Wang, Bo Du, Jiawei Jiang
ICDE 2024
2023
- Angel-PTM: A Scalable and Economical Large-scale Pre-training System in Tencent
Xiaonan Nie, Yi Liu, Fangcheng Fu#, Jinbao Xue, Dian Jiao, Xupeng Miao, Yangyu Tao, Bin Cui#
VLDB 2023 - OSDP: Optimal Sharded Data Parallel for Distributed Deep Learning
Youhe Jiang, Fangcheng Fu#, Xupeng Miao, Xiaonan Nie, Bin Cui#
IJCAI 2023 - KVSAgg: Secure Aggregation of Distributed Key-Value Sets
Yuhan Wu, Siyuan Dong, Yi Zhou, Yikai Zhao, Fangcheng Fu, Tong Yang, Chaoyue Niu, Fan Wu, Bin Cui
ICDE 2023 - P2CG: A Privacy Preserving Collaborative Graph Neural Network Training Framework
Xupeng Miao, Wentao Zhang, Yuezihan Jiang, Fangcheng Fu, Yingxia Shao, Lei Chen, Yangyu Tao, Gang Cao, Bin Cui
VLDB Journal 32(4): 717-736 (2023) - Accelerating Text-to-image Editing via Cache-enabled Sparse Diffusion Inference
Zihao Yu, Haoyang Li, Fangcheng Fu, Xupeng Miao, Bin Cui
MLSys Workshop NeurIPS 2023
2022
- Towards Communication-efficient Vertical Federated Learning Training via Cache-enabled Local Update
Fangcheng Fu, Xupeng Miao, Jiawei Jiang, Huanran Xue, Bin Cui
VLDB 2022 - BlindFL: Vertical Federated Machine Learning without Peeking into Your Data
Fangcheng Fu, Huanran Xue, Yong Cheng, Yangyu Tao, Bin Cui
SIGMOD 2022 - VF-PS: How to Select Important Participants in Vertical Federated Learning, Efficiently and Securely?
Jiawei Jiang, Lukas Burkhalter, Fangcheng Fu, Bo Li, Bolin Ding, Bo Du, Anwar Hithnawi, Ce Zhang
NeurIPS 2022 - Analyzing Online Transaction Networks with Network Motifs
Jiawei Jiang, Yusong Hu, Xiaosen Li, Wen Ouyang, Zhitao Wang, Fangcheng Fu, Bin Cui
SIGKDD 2022 - K-Core Decomposition on Super Large Graphs with Limited Resources
Shicheng Gao, Jie Xu, Xiaosen Li, Fangcheng Fu, Wentao Zhang, Wen Ouyang, Yangyu Tao, Bin Cui
ACM SAC 2022
2021
- VF2Boost: Very Fast Vertical Federated Gradient Boosting for Cross-Enterprise Learning
Fangcheng Fu, Yingxia Shao, Lele Yu, Jiawei Jiang, Huanran Xue, Yangyu Tao, Bin Cui
SIGMOD 2021
2020
- Don’t Waste Your Bits! Squeeze Activations and Gradients for Deep Neural Networks via TinyScript
Fangcheng Fu, Yuzheng Hu, Yihan He, Jiawei Jiang, Yingxia Shao, Ce Zhang, Bin Cui
ICML 2020 - SKCompress: Compressing Sparse and Nonuniform Gradient in Distributed Machine Learning
Jiawei Jiang*, Fangcheng Fu*, Tong Yang, Yingxia Shao, Bin Cui
VLDB Journal 29(5): 945-972 (2020)
2019
- An Experimental Evaluation of Large Scale GBDT Systems
Fangcheng Fu, Jiawei Jiang, Yingxia Shao, Bin Cui
VLDB 2019
2018
- SketchML: Accelerating Distributed Machine Learning with Data Sketches
Jiawei Jiang, Fangcheng Fu, Tong Yang, Bin Cui
SIGMOD 2018 - DimBoost: Boosting Gradient Boosting Tree to Higher Dimensions
Jiawei Jiang, Bin Cui, Ce Zhang, Fangcheng Fu
SIGMOD 2018
Papers in Chinese
- MQLserve：基于量化的多任务大语言模型服务系统/MQLserve: Quantization-based Multi-task LLM serve system
符芳诚,夏义扉,崔斌/Fangcheng Fu, Yifei Xia, Bin Cui
计算机学报/Chinese Journal of Computers (To appear), NDBC 2024 Best Paper - 面向高维特征和多分类的分布式梯度提升树/Distributed Gradient Boosting Decision Tree Algorithm for High-dimensional and Multi-classification Problems
江佳伟,符芳诚,邵蓥侠,崔斌/Jiawei Jiang, Fangcheng Fu, Yingxia Shao, Bin Cui
软件学报/Journal of Software, 2019, 30(3):784-798
Patents
- 基于深度神经网络最小方差梯度量化压缩及图像处理方法. ZL 2019 1 1029711.0
- 一种数据处理方法、装置、设备及计算机可读存储介质. ZL 2021 1 0576191.6
- 基于联邦学习的数据传输方法、装置以及可读存储介质. ZL 2021 1 0680161.X
- 基于联邦神经网络模型的数据处理方法、相关设备及介质. ZL 2021 1 0531392.4
- 联邦模型训练方法、装置、终端设备以及存储介质. ZL 2022 1 0363190.8
- 多方安全计算方法、装置、设备及存储介质. ZL 2021 1 0503941.7
- 联邦神经网络模型的训练方法、装置、设备及存储介质. ZL 2020 1 1167325.0
- 数据集合处理方法、数据处理方法、装置及存储介质. ZL 2021 1 0541183.8