24 citations · 27 across the 2 of their papers we have counts for
2 papers
cs.LG2024★ 24 cited
MoE-Mamba: Efficient Selective State Space Models with Mixture of Experts
Maciej Pióro, Kamil Ciebiera, Krystian Król +7
State Space Models (SSMs) have become serious contenders in the field of sequential modeling, challenging the dominance of Transformers. At the same time, Mixture of Experts (MoE)…
cs.LG2024★ 3 cited
Scaling Laws for Fine-Grained Mixture of Experts
Jakub Krajewski, Jan Ludziejewski, Kamil Adamczewski +9
Mixture of Experts (MoE) models have emerged as a primary solution for reducing the computational cost of Large Language Models. In this work, we analyze their scaling properties,…