Summary of Groupdebate: Enhancing the Efficiency Of Multi-agent Debate Using Group Discussion, by Tongxuan Liu et al.
GroupDebate: Enhancing the Efficiency of Multi-Agent Debate Using Group Discussion
by Tongxuan Liu, Xingyu Wang, Weizhe Huang, Wenjiang Xu, Yuting Zeng, Lei Jiang, Hailong Yang, Jing Li
First submitted to arxiv on: 21 Sep 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 The proposed method reduces token cost in multi-agent debates for logical reasoning tasks by dividing agents into groups, sharing interim results between groups. This approach achieves up to a 51.7% reduction in total tokens used during debates, while potentially enhancing accuracy by as much as 25%. The method demonstrates improved performance and efficiency in multi-agent debate interactions. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper makes it possible for machines to have more efficient conversations with each other. It’s like a team project where each person does their part and then shares what they found with the others. This way, the computers can talk about ideas and find the best answer together. The new method works really well and could be used in many different situations where computers need to work together. |
Keywords
» Artificial intelligence » Token
