2 papers
cs.LG2026
FedOBP: Federated Optimal Brain Personalization through Cloud-Edge Element-wise Decoupling
Xingyan Chen, Tian Du, Changqiao Xu +4
Federated Learning (FL) faces challenges from client data heterogeneity and resource-constrained mobile devices, which can degrade model accuracy. Personalized Federated Learning (…
cs.DC2026
Huawei Cloud Model-as-a-Service on the CloudMatrix384 SuperPod
Ao Xiao, Bangzheng He, Baoquan Zhang +125
Scaled-out MoE LLMs and scaled-up SuperPods create new systems challenges for production Model-as-a-Service (MaaS), requiring disaggregation, low-latency communication, and decentr…