Xuanwen Huang
2024
An Expert is Worth One Token: Synergizing Multiple Expert LLMs as Generalist via Expert Token Routing
Ziwei Chai
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Guoyin Wang
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Jing Su
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Tianjie Zhang
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Xuanwen Huang
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Xuwu Wang
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Jingjing Xu
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Jianbo Yuan
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Hongxia Yang
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Fei Wu
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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.
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Co-authors
- Ziwei Chai 1
- Guoyin Wang 1
- Jing Su 1
- Tianjie Zhang 1
- Xuwu Wang 1
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