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On the Discussion of Large Language Models: Symmetry of Agents and Interplay with Prompts

Authors :
Wang, Qineng
Wang, Zihao
Su, Ying
Song, Yangqiu
Publication Year :
2023

Abstract

Two ways has been discussed to unlock the reasoning capability of a large language model. The first one is prompt engineering and the second one is to combine the multiple inferences of large language models, or the multi-agent discussion. Theoretically, this paper justifies the multi-agent discussion mechanisms from the symmetry of agents. Empirically, this paper reports the empirical results of the interplay of prompts and discussion mechanisms, revealing the empirical state-of-the-art performance of complex multi-agent mechanisms can be approached by carefully developed prompt engineering. This paper also proposes a scalable discussion mechanism based on conquer and merge, providing a simple multi-agent discussion solution with simple prompts but state-of-the-art performance.<br />Comment: Working in progress, and code will be released soon

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2311.07076
Document Type :
Working Paper