The paper Branch-Train-MiX: Mixing Expert LLMs into a Mixture-of-Experts LLM explores the training of Large Language Models (LLMs) to become proficient in multiple specialized domains. Branch-Train-MiX (BTX) is an innovative approach that branches a seed model into different domains, followed by an MoE-finetuning stage for task-specific token-level routing.

Core concepts include:

• Parallel training of multiple domain experts
• Integration into Mixture-of-Expert layers
• Best accuracy-efficiency tradeoff

BTX method may disrupt traditional language model training by offering a scalable and targeted solution to build highly specialized language capabilities. The research is presented on arXiv.