Xuanwen Huang


2024

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An Expert is Worth One Token: Synergizing Multiple Expert LLMs as Generalist via Expert Token Routing
Ziwei Chai | Guoyin Wang | Jing Su | Tianjie Zhang | Xuanwen Huang | Xuwu Wang | Jingjing Xu | Jianbo Yuan | Hongxia Yang | Fei Wu | Yang Yang
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

We present Expert-Token-Routing, a unified generalist framework that facilitates seamless integration of multiple expert LLMs. Our framework represents expert LLMs as special expert tokens within the vocabulary of a meta LLM. The meta LLM can route to an expert LLM like generating new tokens. Expert-Token-Routing not only supports learning the implicit expertise of expert LLMs from existing instruction dataset but also allows for dynamic extension of new expert LLMs in a plug-and-play manner. It also conceals the detailed collaboration process from the user’s perspective, facilitating interaction as though it were a singular LLM. Our framework outperforms various existing multi-LLM collaboration paradigms across benchmarks that incorporate six diverse expert domains, demonstrating effectiveness and robustness in building generalist LLM system via synergizing multiple expert LLMs.