More Effective Distributed Deep Learning Using Staleness Based Parameter Updating. - Yan Ye; Mengqiang Chen; Zijie Yan; Weigang Wu; Nong Xiao 001 (ICA3PP (2), 2018)

Gradient Sparification for Asynchronous Distributed Training. - Zijie Yan (CoRR, 2019)

Standard Deviation Based Adaptive Gradient Compression For Distributed Deep Learning. - Mengqiang Chen; Zijie Yan; Jiangtao Ren; Weigang Wu (CCGRID, 2020)

Dual-Way Gradient Sparsification for Asynchronous Distributed Deep Learning. - Zijie Yan; Danyang Xiao; Mengqiang Chen; Jieying Zhou; Weigang Wu (ICPP, 2020)

Upcycling Large Language Models into Mixture of Experts. - Ethan He; Abhinav Khattar; Ryan Prenger; Vijay Korthikanti; Zijie Yan; Tong Liu; Shiqing Fan; Ashwath Aithal; Mohammad Shoeybi; Bryan Catanzaro (CoRR, 2024)

Llama 3 Meets MoE: Efficient Upcycling. - Aditya Vavre; Ethan He; Dennis Liu; Zijie Yan; June Yang; Nima Tajbakhsh; Ashwath Aithal (CoRR, 2024)

MoE Parallel Folding: Heterogeneous Parallelism Mappings for Efficient Large-Scale MoE Model Training with Megatron Core. - Dennis Liu; Zijie Yan; Xin Yao; Tong Liu; Vijay Korthikanti; Evan Wu; Shiqing Fan; Gao Deng; Hongxiao Bai; Jianbin Chang; Ashwath Aithal; Michael Andersch; et al. (CoRR, 2025)