4 papers
SlimCaching: Edge Caching of Mixture-of-Experts for Distributed Inference
Qian Chen, Xianhao Chen, Kaibin Huang
Mixture-of-Experts (MoE) models improve the scalability of large language models (LLMs) by activating only a small subset of relevant experts per input. However, the sheer number o…
PartialLoading: User Scheduling and Bandwidth Allocation for Parameter-sharing Edge Inference
Guanqiao Qu, Qian Chen, Xianhao Chen +2
By provisioning inference offloading services, edge inference drives the rapid growth of AI applications at network edge. However, how to reduce the inference latency remains a sig…
FedMeld: A Model-dispersal Federated Learning Framework for Space-ground Integrated Networks
Qian Chen, Xianhao Chen, Kaibin Huang
To bridge the digital divide, space-ground integrated networks (SGINs) are expected to deliver artificial intelligence (AI) services to every corner of the world. One key mission o…
Space-ground Fluid AI for 6G Edge Intelligence
Qian Chen, Zhanwei Wang, Xianhao Chen +5
Edge artificial intelligence (AI) and space-ground integrated networks (SGINs) are two main usage scenarios of the sixth-generation (6G) mobile networks. Edge AI supports pervasive…