11 citations · 13 across the 9 of their papers we have counts for
4 papers · 1 filter
BALANCE: Hybrid Autoregressive-Speculative LLM Inference at the Network Edge
Guanqiao Qu, Shuo Chen, Qian Chen +2
Edge inference is a promising paradigm to provide large language model (LLM) inference services in next-generation mobile networks. LLM inference mainly relies on two approaches: A…
SpaceMoE: Towards Orbital General Intelligence with Distributed Mixture-of-Experts Inference
Qian Chen, Xianhao Chen, Min Sheng +1
As satellite networks evolve to support increasingly diverse services and artificial general intelligence (AGI), large language models (LLMs) are emerging as a critical foundation…
SLIDE: Simultaneous Model Downloading and Inference at the Wireless Network Edge
Guanqiao Qu, Tao Li, Qian Chen +2
To support on-device inference, the next-generation mobile networks are expected to support real-time model downloading services to mobile users. However, powerful AI models typica…
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…