2 papers
cs.DC2026
Stable-MoE: Lyapunov-based Token Routing for Distributed Mixture-of-Experts Training over Edge Networks
Long Shi, Bingyan Ou, Kang Wei +3
The sparse activation mechanism of mixture of experts (MoE) model empowers edge intelligence with enhanced training efficiency and reduced computational resource consumption. Howev…
cs.DC2025
When MoE Meets Blockchain: A Trustworthy Distributed Framework of Large Models
Weihao Zhu, Long Shi, Kang Wei +4
As an enabling architecture of Large Models (LMs), Mixture of Experts (MoE) has become prevalent thanks to its sparsely-gated mechanism, which lowers computational overhead while m…