Summary of An Expert Is Worth One Token: Synergizing Multiple Expert Llms As Generalist Via Expert Token Routing, by Ziwei Chai et al.
An Expert is Worth One Token: Synergizing Multiple Expert LLMs as Generalist via Expert Token Routing
by Ziwei Chai, Guoyin Wang, Jing Su, Tianjie Zhang, Xuanwen Huang, Xuwu Wang, Jingjing Xu, Jianbo Yuan, Hongxia Yang, Fei Wu, Yang Yang
First submitted to arxiv on: 25 Mar 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper introduces Expert-Token-Routing, a unified framework for combining multiple language model large models (LLMs) to create a generalist model. The framework represents each expert LLM as a special token within the vocabulary of a meta LLM, allowing it to route to an expert LLM like generating new tokens. This enables learning from existing instruction datasets and dynamic extension of new expert LLMs in a plug-and-play manner. The framework outperforms existing multi-LLM collaboration paradigms across benchmarks covering six diverse domains. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper is about using many language models together to make a better one. It’s like having multiple experts working together, but the user doesn’t have to worry about how they’re working together – it just looks like one expert is helping them. The paper shows that this way of combining experts works well and can be used in different areas like science, history, or technology. |
Keywords
» Artificial intelligence » Language model » Token
