Two-Dimensional Learning Rate Decay: Towards Accurate Federated Learning with Non-IID Data. - Kaiwei Mo; Chen Chen 067; Jiamin Li 002; Hong Xu 001; Chun Jason Xue (IJCNN, 2021)

Aryl: An Elastic Cluster Scheduler for Deep Learning. - Jiamin Li 002; Hong Xu 001; Yibo Zhu; Zherui Liu; Chuanxiong Guo; Cong Wang 001 (CoRR, 2022)

Lita: Accelerating Distributed Training of Sparsely Activated Models. - Jiamin Li 002; Yimin Jiang; Yibo Zhu; Cong Wang 001; Hong Xu 001 (CoRR, 2022)

ScaleFlux: Efficient Stateful Scaling in NFV. - Libin Liu 001; Hong Xu 001; Zhixiong Niu; Jingzong Li; Wei Zhang 049; Peng Wang 037; Jiamin Li 002; Chun Jason Xue; Cong Wang 001 (IEEE Trans. Parallel Distributed Syst., 2022)

Adaptive Gating in Mixture-of-Experts based Language Models. - Jiamin Li 002; Qiang Su; Yitao Yang; Yimin Jiang; Cong Wang 001; Hong Xu 001 (EMNLP, 2023)

Lyra: Elastic Scheduling for Deep Learning Clusters. - Jiamin Li 002; Hong Xu 001; Yibo Zhu; Zherui Liu; Chuanxiong Guo; Cong Wang 001 (EuroSys, 2023)

Accelerating Distributed MoE Training and Inference with Lina. - Jiamin Li 002; Yimin Jiang; Yibo Zhu; Cong Wang 001; Hong Xu 001 (USENIX ATC, 2023)

Bottleneck-Aware Non-Clairvoyant Coflow Scheduling With Fai. - Libin Liu 001; Chengxi Gao; Peng Wang 037; Hongming Huang; Jiamin Li 002; Hong Xu 001; Wei Zhang 049 (IEEE Trans. Cloud Comput., 2023)

Arlo: Serving Transformer-based Language Models with Dynamic Input Lengths. - Xin Tan 004; Jiamin Li 002; Yitao Yang; Jingzong Li; Hong Xu 001 (ICPP, 2024)

BlockLLM: Multi-tenant Finer-grained Serving for Large Language Models. - Jiamin Li 002; Le Xu; Hong Xu 001; Aditya Akella (CoRR, 2024)

StitchLLM: Serving LLMs, One Block at a Time. - Bodun Hu; Shuozhe Li; Saurabh Agarwal; Myungjin Lee; Akshay Jajoo; Jiamin Li 002; Le Xu; Geon-Woo Kim; Donghyun Kim 002; Hong Xu 001; Amy Zhang 001; Aditya Akella (ACL (1), 2025)