Learning cascaded influence under partial monitoring. - Jie Zhang 078; Jiaqi Ma 001; Jie Tang 001 (ASONAM, 2016)

Semi-supervised Learning on Graphs with Generative Adversarial Nets. - Ming Ding 004; Jie Tang 001; Jie Zhang 078 (CIKM, 2018)

Spectral Network Embedding: A Fast and Scalable Method via Sparsity. - Jie Zhang 078; Yan Wang 120; Jie Tang 001; Ming Ding 004 (CoRR, 2018)

A Fast Network Embedding Approach with Preserving Hierarchical Proximities. - Jie Zhang 078; Yan Wang 120; Jie Tang 001 (DSC, 2019)

ProNE: Fast and Scalable Network Representation Learning. - Jie Zhang 078; Yuxiao Dong; Yan Wang 120; Jie Tang 001; Ming Ding 004 (IJCAI, 2019)

OAG: Toward Linking Large-scale Heterogeneous Entity Graphs. - Fanjin Zhang; Xiao Liu 036; Jie Tang 001; Yuxiao Dong; Peiran Yao; Jie Zhang 078; Xiaotao Gu; Yan Wang 120; Bin Shao; Rui Li; Kuansan Wang (KDD, 2019)

Graph Random Neural Networks for Semi-Supervised Learning on Graphs. - Wenzheng Feng; Jie Zhang 078; Yuxiao Dong; Yu Han 001; Huanbo Luan; Qian Xu 005; Qiang Yang 001; Evgeny Kharlamov; Jie Tang 001 (NeurIPS, 2020)

Graph Random Neural Network. - Wenzheng Feng; Jie Zhang 078; Yuxiao Dong; Yu Han 001; Huanbo Luan; Qian Xu 005; Qiang Yang 001; Jie Tang 001 (CoRR, 2020)

Whale: A Unified Distributed Training Framework. - Ang Wang; Xianyan Jia; Le Jiang; Jie Zhang 078; Yong Li 020; Wei Lin 016 (CoRR, 2020)

M6: A Chinese Multimodal Pretrainer. - Junyang Lin; Rui Men; An Yang; Chang Zhou; Ming Ding 004; Yichang Zhang; Peng Wang 028; Ang Wang; Le Jiang; Xianyan Jia; Jie Zhang 078; Jianwei Zhang 012; et al. (CoRR, 2021)

Exploring Sparse Expert Models and Beyond. - An Yang; Junyang Lin; Rui Men; Chang Zhou; Le Jiang; Xianyan Jia; Ang Wang; Jie Zhang 078; Jiamang Wang; Yong Li 020; Di Zhang; Wei Lin 016; et al. (CoRR, 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 078; Yong Li 020; Wei Lin 016; Jingren Zhou 001; Hongxia Yang (CoRR, 2021)

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 078; Jiamang Wang; Jianbo Dong; Yunlong Xu; Yue Song; Yong Li 020; Di Zhang; et al. (ICDE, 2022)

Whale: Efficient Giant Model Training over Heterogeneous GPUs. - Xianyan Jia; Le Jiang; Ang Wang; Wencong Xiao; Ziji Shi; Jie Zhang 078; Xinyuan Li; Langshi Chen; Yong Li 020; Zhen Zheng; Xiaoyong Liu; Wei Lin 016 (USENIX ATC, 2022)

TAP: Accelerating Large-Scale DNN Training Through Tensor Automatic Parallelisation. - Ziji Shi; Le Jiang; Ang Wang; Jie Zhang 078; Xianyan Jia; Yong Li 020; Chencan Wu; Jialin Li; Wei Lin 016 (CoRR, 2023)

Automated Unsupervised Graph Representation Learning. - Zhenyu Hou; Yukuo Cen; Yuxiao Dong; Jie Zhang 078; Jie Tang 001 (IEEE Trans. Knowl. Data Eng., 2023)

OAG: Linking Entities Across Large-Scale Heterogeneous Knowledge Graphs. - Fanjin Zhang; Xiao Liu 036; Jie Tang 001; Yuxiao Dong; Peiran Yao; Jie Zhang 078; Xiaotao Gu; Yan Wang 120; Evgeny Kharlamov; Bin Shao; Rui Li; Kuansan Wang (IEEE Trans. Knowl. Data Eng., 2023)

Unlearning during Learning: An Efficient Federated Machine Unlearning Method. - Hanlin Gu; Gongxi Zhu; Jie Zhang 078; Xinyuan Zhao; Yuxing Han 001; Lixin Fan; Qiang Yang 001 (IJCAI, 2024)

Contextual Generative Auction with Permutation-level Externalities for Online Advertising. - Ruitao Zhu; Yangsu Liu; Dagui Chen; Zhenjia Ma; Chufeng Shi; Zhenzhe Zheng; Jie Zhang 078; Jian Xu 015; Bo Zheng 007; Fan Wu 006 (KDD (1), 2025)

Efficient Long Context Fine-tuning with Chunk Flow. - Xiulong Yuan; Hongtao Xu; Wenting Shen; Ang Wang; Xiafei Qiu; Jie Zhang 078; Yuqiong Liu; Bowen Yu 002; Junyang Lin; Mingzhen Li 001; Weile Jia; Yong Li 020; et al. (CoRR, 2025)