Token Expert Combination

Token expert combination, a key aspect of Mixture-of-Experts (MoE) models, aims to efficiently distribute computational load across multiple specialized "expert" networks within large language models. Current research focuses on improving routing algorithms, such as recurrent routers that leverage information across layers, and developing more stable routing strategies to mitigate training instability and enhance efficiency. These advancements are significant because they enable scaling model size without a proportional increase in computational cost, leading to improved performance in various natural language processing and other tasks.