@inproceedings{chai-etal-2024-expert,
title = "An Expert is Worth One Token: Synergizing Multiple Expert {LLM}s as Generalist via Expert Token Routing",
author = "Chai, Ziwei and
Wang, Guoyin and
Su, Jing and
Zhang, Tianjie and
Huang, Xuanwen and
Wang, Xuwu and
Xu, Jingjing and
Yuan, Jianbo and
Yang, Hongxia and
Wu, Fei and
Yang, Yang",
editor = "Ku, Lun-Wei and
Martins, Andre and
Srikumar, Vivek",
booktitle = "Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
month = aug,
year = "2024",
address = "Bangkok, Thailand",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.acl-long.614",
pages = "11385--11396",
abstract = "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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<abstract>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.</abstract>
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%0 Conference Proceedings
%T An Expert is Worth One Token: Synergizing Multiple Expert LLMs as Generalist via Expert Token Routing
%A Chai, Ziwei
%A Wang, Guoyin
%A Su, Jing
%A Zhang, Tianjie
%A Huang, Xuanwen
%A Wang, Xuwu
%A Xu, Jingjing
%A Yuan, Jianbo
%A Yang, Hongxia
%A Wu, Fei
%A Yang, Yang
%Y Ku, Lun-Wei
%Y Martins, Andre
%Y Srikumar, Vivek
%S Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
%D 2024
%8 August
%I Association for Computational Linguistics
%C Bangkok, Thailand
%F chai-etal-2024-expert
%X 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.
%U https://aclanthology.org/2024.acl-long.614
%P 11385-11396
Markdown (Informal)
[An Expert is Worth One Token: Synergizing Multiple Expert LLMs as Generalist via Expert Token Routing](https://aclanthology.org/2024.acl-long.614) (Chai et al., ACL 2024)
ACL
- Ziwei Chai, Guoyin Wang, Jing Su, Tianjie Zhang, Xuanwen Huang, Xuwu Wang, Jingjing Xu, Jianbo Yuan, Hongxia Yang, Fei Wu, and Yang Yang. 2024. An Expert is Worth One Token: Synergizing Multiple Expert LLMs as Generalist via Expert Token Routing. In Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 11385–11396, Bangkok, Thailand. Association for Computational Linguistics.