# 🤖 More Agents Is All You Need

Source: https://arxiv.org/abs/2402.05120
Kiwi News: https://news.kiwistand.com/stories/More-Agents-Is-All-You-Need?index=0x65c8a141a3566a4967b338d9701c19cc981cd3218e79734b55a7b31070b8491318f19783
Submitted by frotograf.eth on 2024-02-11 UTC, 1 upvote, 0 comments

## Summary

The paper reports that simple sampling-and-voting across multiple agents improves large language model performance, and that this performance scales with the number of agents instantiated. The method, called Agent Forest, is orthogonal to existing more complicated methods for enhancing LLMs, and the size of the gain is correlated with task difficulty. The authors, Junyou Li, Qin Zhang, Yangbin Yu, Qiang Fu and Deheng Ye, say they ran comprehensive experiments on a wide range of LLM benchmarks to verify this finding and study the properties that facilitate it. Their code is publicly available.

## Article

More Agents Is All You Need

Authors: Junyou Li, Qin Zhang, Yangbin Yu, Qiang Fu, Deheng Ye

We find that, simply via a sampling-and-voting method, the performance of large language models (LLMs) scales with the number of agents instantiated. Also, this method, termed as Agent Forest, is orthogonal to existing complicated methods to further enhance LLMs, while the degree of enhancement is correlated to the task difficulty. We conduct comprehensive experiments on a wide range of LLM benchmarks to verify the presence of our finding, and to study the properties that can facilitate its occurrence. Our code is publicly available at: this https URL