Mixture of Experts (MoE) Decoded: Mastering Sparse/Dense Gating and Multimodal AI Architectures

Mixture of Experts (MoE) and Mixture of Multimodal Experts (MoME): A Curated Overview Keywords: Mixture of Experts, MoE, MoME, Sparse Gating, Dense Gating, Soft Gating, Expert Splitting, Token Merging, Parameter-Efficient Fine-Tuning, Auxiliary Loss, Capacity Limit Introduction The Mixture of Experts (MoE) paradigm has emerged as a leading approach to scale deep learning models efficiently. By dynamically routing inputs to specialized submodels—experts—MoE architectures achieve conditional computation: only a subset of experts is activated per input. This design enables models to grow to billions or even trillions of parameters while keeping inference and training costs manageable. More recently, the concept has extended …