2 citations · 4 across the 2 of their papers we have counts for
2 papers
cs.CL2024★ 2 cited
HMoE: Heterogeneous Mixture of Experts for Language Modeling
An Wang, Xingwu Sun, Ruobing Xie +9
Mixture of Experts (MoE) offers remarkable performance and computational efficiency by selectively activating subsets of model parameters. Traditionally, MoE models use homogeneous…
cs.LG2024★ 2 cited
MEMO: Fine-grained Tensor Management For Ultra-long Context LLM Training
Pinxue Zhao, Hailin Zhang, Fangcheng Fu +9
Nowadays, Large Language Models (LLMs) have been trained using extended context lengths to foster more creative applications. However, long context training poses great challenges…