DimBoost: Boosting Gradient Boosting Decision Tree to Higher Dimensions. - Jiawei Jiang 001; Bin Cui 001; Ce Zhang 001; Fangcheng Fu (SIGMOD Conference, 2018)

SketchML: Accelerating Distributed Machine Learning with Data Sketches. - Jiawei Jiang 001; Fangcheng Fu; Tong Yang 003; Bin Cui 001 (SIGMOD Conference, 2018)

An Experimental Evaluation of Large Scale GBDT Systems. - Fangcheng Fu; Jiawei Jiang 001; Yingxia Shao; Bin Cui 001 (Proc. VLDB Endow., 2019)

Don't Waste Your Bits! Squeeze Activations and Gradients for Deep Neural Networks via TinyScript. - Fangcheng Fu; Yuzheng Hu; Yihan He; Jiawei Jiang 001; Yingxia Shao; Ce Zhang 001; Bin Cui 001 (ICML, 2020)

SKCompress: compressing sparse and nonuniform gradient in distributed machine learning. - Jiawei Jiang 001; Fangcheng Fu; Tong Yang 003; Yingxia Shao; Bin Cui 001 (VLDB J., 2020)

VF2Boost: Very Fast Vertical Federated Gradient Boosting for Cross-Enterprise Learning. - Fangcheng Fu; Yingxia Shao; Lele Yu; Jiawei Jiang 001; Huanran Xue; Yangyu Tao; Bin Cui 001 (SIGMOD Conference, 2021)

Analyzing Online Transaction Networks with Network Motifs. - Jiawei Jiang 001; Yusong Hu; Xiaosen Li; Wen Ouyang; Zhitao Wang; Fangcheng Fu; Bin Cui 001 (KDD, 2022)

VF-PS: How to Select Important Participants in Vertical Federated Learning, Efficiently and Securely? - Jiawei Jiang 001; Lukas Burkhalter; Fangcheng Fu; Bolin Ding; Bo Du 001; Anwar Hithnawi; Bo Li 026; Ce Zhang 001 (NeurIPS, 2022)

K-core decomposition on super large graphs with limited resources. - Shicheng Gao; Jie Xu 007; Xiaosen Li; Fangcheng Fu; Wentao Zhang 001; Wen Ouyang; Yangyu Tao; Bin Cui 001 (SAC, 2022)

BlindFL: Vertical Federated Machine Learning without Peeking into Your Data. - Fangcheng Fu; Huanran Xue; Yong Cheng; Yangyu Tao; Bin Cui 001 (SIGMOD Conference, 2022)

Towards Communication-efficient Vertical Federated Learning Training via Cache-enabled Local Updates. - Fangcheng Fu; Xupeng Miao; Jiawei Jiang 001; Huanran Xue; Bin Cui 001 (CoRR, 2022)

Towards Communication-efficient Vertical Federated Learning Training via Cache-enabled Local Update. - Fangcheng Fu; Xupeng Miao; Jiawei Jiang 001; Huanran Xue; Bin Cui 001 (Proc. VLDB Endow., 2022)

KVSAgg: Secure Aggregation of Distributed Key-Value Sets. - Yuhan Wu 001; Siyuan Dong; Yi Zhou; Yikai Zhao 001; Fangcheng Fu; Tong Yang 003; Chaoyue Niu; Fan Wu 006; Bin Cui 001 (ICDE, 2023)

OSDP: Optimal Sharded Data Parallel for Distributed Deep Learning. - Youhe Jiang; Fangcheng Fu; Xupeng Miao; Xiaonan Nie; Bin Cui 001 (IJCAI, 2023)

FISEdit: Accelerating Text-to-image Editing via Cache-enabled Sparse Diffusion Inference. - Zihao Yu; Haoyang Li; Fangcheng Fu; Xupeng Miao; Bin Cui 001 (CoRR, 2023)

Improving Automatic Parallel Training via Balanced Memory Workload Optimization. - Yujie Wang; Youhe Jiang; Xupeng Miao; Fangcheng Fu; Xiaonan Nie; Bin Cui 001 (CoRR, 2023)

Generative and Contrastive Paradigms Are Complementary for Graph Self-Supervised Learning. - Yuxiang Wang; Xiao Yan 002; Chuang Hu; Fangcheng Fu; Wentao Zhang 001; Hao Wang 013; Shuo Shang; Jiawei Jiang 001 (CoRR, 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 001 (Proc. VLDB Endow., 2023)

P2CG: a privacy preserving collaborative graph neural network training framework. - Xupeng Miao; Wentao Zhang 001; Yuezihan Jiang; Fangcheng Fu; Yingxia Shao; Lei Chen 002; Yangyu Tao; Gang Cao; Bin Cui 001 (VLDB J., 2023)

Accelerating Text-to-Image Editing via Cache-Enabled Sparse Diffusion Inference. - Zihao Yu; Haoyang Li; Fangcheng Fu; Xupeng Miao; Bin Cui 001 (AAAI, 2024)

Generative and Contrastive Paradigms Are Complementary for Graph Self-Supervised Learning. - Yuxiang Wang; Xiao Yan 002; Chuang Hu; Quanqing Xu; Chuanhui Yang; Fangcheng Fu; Wentao Zhang 001; Hao Wang 013; Bo Du 001; Jiawei Jiang 001 (ICDE, 2024)

X-former Elucidator: Reviving Efficient Attention for Long Context Language Modeling. - Xupeng Miao; Shenhan Zhu; Fangcheng Fu; Ziyu Guo; Zhi Yang 001; Yaofeng Tu; Zhihao Jia; Bin Cui 001 (IJCAI, 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 001 (NeurIPS, 2024)

Efficient Multi-task LLM Quantization and Serving for Multiple LoRA Adapters. - Yifei Xia; Fangcheng Fu; Wentao Zhang 001; Jiawei Jiang 001; Bin Cui 001 (NeurIPS, 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 004; Xupeng Miao; Bin Cui 001 (SOSP, 2024)

Retrieval-Augmented Generation for AI-Generated Content: A Survey. - Penghao Zhao; Hailin Zhang 004; Qinhan Yu; Zhengren Wang; Yunteng Geng; Fangcheng Fu; Ling Yang 006; Wentao Zhang 001; Bin Cui 001 (CoRR, 2024)

Efficiently Training 7B LLM with 1 Million Sequence Length on 8 GPUs. - Pinxue Zhao; Hailin Zhang 004; Fangcheng Fu; Xiaonan Nie; Qibin Liu; Fang Yang; Yuanbo Peng; Dian Jiao; Shuaipeng Li; Jinbao Xue; Yangyu Tao; Bin Cui 001 (CoRR, 2024)

Efficient Multi-Task Large Model Training via Data Heterogeneity-aware Model Management. - Yujie Wang; Shenhan Zhu; Fangcheng Fu; Xupeng Miao; Jie Zhang; Juan Zhu; Fan Hong; Yong Li; Bin Cui 001 (CoRR, 2024)

Retrofitting Temporal Graph Neural Networks with Transformer. - Qiang Huang 009; Xiao Yan 002; Xin Wang 128; Susie Xi Rao; Zhichao Han 001; Fangcheng Fu; Wentao Zhang 001; Jiawei Jiang 001 (CoRR, 2024)

Gradual Learning: Optimizing Fine-Tuning with Partially Mastered Knowledge in Large Language Models. - Bozhou Li; Hao Liang; Yang Li 140; Fangcheng Fu; Hongzhi Yin; Conghui He; Wentao Zhang 001 (CoRR, 2024)

Data-Centric and Heterogeneity-Adaptive Sequence Parallelism for Efficient LLM Training. - Yujie Wang; Shiju Wang; Shenhan Zhu; Fangcheng Fu; Xinyi Liu; Xuefeng Xiao 001; Huixia Li; Jiashi Li; Faming Wu; Bin Cui 001 (CoRR, 2024)

Demystifying Workload Imbalances in Large Transformer Model Training over Variable-length Sequences. - Haoyang Li; Fangcheng Fu; Sheng Lin; Hao Ge; Xuanyu Wang; Jiawen Niu; Jie Jiang 015; Bin Cui 001 (CoRR, 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 001 (IEEE Trans. Knowl. Data Eng., 2024)

ProjPert: Projection-Based Perturbation for Label Protection in Split Learning Based Vertical Federated Learning. - Fangcheng Fu; Xuanyu Wang; Jiawei Jiang 001; Huanran Xue; Bin Cui 001 (IEEE Trans. Knowl. Data Eng., 2024)

HaCore: Efficient Coreset Construction with Locality Sensitive Hashing for Vertical Federated Learning. - Qinbo Zhang; Xiao Yan 002; Yukai Ding; Fangcheng Fu; Quanqing Xu; Ziyi Li; Chuang Hu; Jiawei Jiang 001 (AAAI, 2025)

Enhancing Unsupervised Sentence Embeddings via Knowledge-Driven Data Augmentation and Gaussian-Decayed Contrastive Learning. - Peichao Lai; Zhengfeng Zhang; Wentao Zhang 001; Fangcheng Fu; Bin Cui 001 (ACL (1), 2025)

FlexSP: Accelerating Large Language Model Training via Flexible Sequence Parallelism. - Yujie Wang; Shiju Wang; Shenhan Zhu; Fangcheng Fu; Xinyi Liu; Xuefeng Xiao 001; Huixia Li; Jiashi Li; Faming Wu; Bin Cui 001 (ASPLOS (2), 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 001 (ASPLOS (2), 2025)

Towards Scalable and Efficient Graph Structure Learning. - Siqi Shen; Wentao Zhang 001; Chengshuo Du; Chong Chen 001; Fangcheng Fu; Yingxia Shao; Bin Cui 001 (ICDE, 2025)

Hounding Data Diversity: Towards Participant Selection in Vertical Federated Learning. - Xiaokai Zhou; Xiao Yan 002; Fangcheng Fu; Xinyan Li; Hao Huang 001; Quanqing Xu; Chuanhui Yang; Bo Du 001; Tieyun Qian; Jiawei Jiang 001 (ICDE, 2025)

NetMoE: Accelerating MoE Training through Dynamic Sample Placement. - Xinyi Liu; Yujie Wang; Fangcheng Fu; Xupeng Miao; Shenhan Zhu; Xiaonan Nie; Bin Cui 001 (ICLR, 2025)

Demystifying Cost-Efficiency in LLM Serving over Heterogeneous GPUs. - Youhe Jiang; Fangcheng Fu; Xiaozhe Yao; Guoliang He; Xupeng Miao; Ana Klimovic; Bin Cui 001; Binhang Yuan; Eiko Yoneki (CoRR, 2025)

ThunderServe: High-performance and Cost-efficient LLM Serving in Cloud Environments. - Youhe Jiang; Fangcheng Fu; Xiaozhe Yao; Taiyi Wang; Bin Cui 001; Ana Klimovic; Eiko Yoneki (CoRR, 2025)

Training-free and Adaptive Sparse Attention for Efficient Long Video Generation. - Yifei Xia; Suhan Ling; Fangcheng Fu; Yujie Wang; Huixia Li; Xuefeng Xiao 001; Bin Cui 001 (CoRR, 2025)

ByteScale: Efficient Scaling of LLM Training with a 2048K Context Length on More Than 12,000 GPUs. - Hao Ge; Junda Feng; Qi Huang; Fangcheng Fu; Xiaonan Nie; Lei Zuo; Haibin Lin; Bin Cui 001; Xin Liu (CoRR, 2025)

MEMO: Fine-grained Tensor Management For Ultra-long Context LLM Training. - Pinxue Zhao; Hailin Zhang 004; Fangcheng Fu; Xiaonan Nie; Qibin Liu; Fang Yang; Yuanbo Peng; Dian Jiao; Shuaipeng Li; Jinbao Xue; Yangyu Tao; Bin Cui 001 (Proc. ACM Manag. Data, 2025)

Detecting and Analyzing Motifs in Large-Scale Online Transaction Networks. - Jiawei Jiang 001; Hao Huang 001; Zhigao Zheng 001; Yi Wei; Fangcheng Fu; Xiaosen Li; Bin Cui 001 (IEEE Trans. Knowl. Data Eng., 2025)

Hetu v2: A General and Scalable Deep Learning System with Hierarchical and Heterogeneous Single Program Multiple Data Annotations. - Haoyang Li; Fangcheng Fu; Hao Ge; Sheng Lin; Xuanyu Wang; Jiawen Niu; Xupeng Miao; Bin Cui 001 (CoRR, 2025)

Galvatron: An Automatic Distributed System for Efficient Foundation Model Training. - Xinyi Liu; Yujie Wang; Shenhan Zhu; Fangcheng Fu; Qingshuo Liu; Guangming Lin; Bin Cui 001 (CoRR, 2025)

LobRA: Multi-tenant Fine-tuning over Heterogeneous Data. - Sheng Lin; Fangcheng Fu; Haoyang Li; Hao Ge; Xuanyu Wang; Jiawen Niu; Yaofeng Tu; Bin Cui 001 (Proc. VLDB Endow., 2025)

Thinking Short and Right Over Thinking Long: Serving LLM Reasoning Efficiently and Accurately. - Yuhang Wang; Youhe Jiang; Bin Cui 001; Fangcheng Fu (CoRR, 2025)

SALE : Low-bit Estimation for Efficient Sparse Attention in Long-context LLM Prefilling. - Xiaodong Ji; Hailin Zhang 004; Fangcheng Fu; Bin Cui 001 (CoRR, 2025)

Cascadia: A Cascade Serving System for Large Language Models. - Youhe Jiang; Fangcheng Fu; Wanru Zhao; Stephan Rabanser; Nicholas D. Lane; Binhang Yuan (CoRR, 2025)

How Significant Are the Real Performance Gains? An Unbiased Evaluation Framework for GraphRAG. - Qiming Zeng; Xiao Yan 002; Hao Luo; Yuhao Lin; Yuxiang Wang; Fangcheng Fu; Bo Du 001; Quanqing Xu; Jiawei Jiang 001 (CoRR, 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 004; Xiaonan Nie; Bin Cui 001 (Proc. ACM Manag. Data, 2025)

PQCache: Product Quantization-based KVCache for Long Context LLM Inference. - Hailin Zhang 004; Xiaodong Ji; Yilin Chen; Fangcheng Fu; Xupeng Miao; Xiaonan Nie; Weipeng Chen; Bin Cui 001 (Proc. ACM Manag. Data, 2025)

Efficient Mixed-Precision Large Language Model Inference with TurboMind. - Li Zhang; Youhe Jiang; Guoliang He; Xin Chen; Han Lv; Qian Yao; Fangcheng Fu; Kai Chen 026 (CoRR, 2025)