Showing cs.LGShow all
2 papers · 1 filter
cs.LG2025
Not All Models Suit Expert Offloading: On Local Routing Consistency of Mixture-of-Expert Models
Jingcong Liang, Siyuan Wang, Miren Tian +3
Mixture-of-Experts (MoE) enables efficient scaling of large language models (LLMs) with sparsely activated experts during inference. To effectively deploy large MoE models on memor…
cs.LG2025
Mixture of Lookup Experts
Shibo Jie, Yehui Tang, Kai Han +4
Mixture-of-Experts (MoE) activates only a subset of experts during inference, allowing the model to maintain low inference FLOPs and latency even as the parameter count scales up.…