More Agents Is All You Need
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 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:
https://anonymous.4open.science/r/more_agent_is_all_you_need.
65c592e52b319ae036ffedf9
Junyou Li
65c592e52b319ae036ffedfa
Qin Zhang
65c592e52b319ae036ffedfb
Yangbin Yu
65c592e52b319ae036ffedfc
Qiang Fu
65c592e52b319ae036ffedfd
Deheng Ye
More Agents Is All You Need
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 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:
https://anonymous.4open.science/r/more_agent_is_all_you_need.
A sampling-and-voting method enhances large language models' performance by increasing the number of agents, with effectiveness tied to task difficulty.
large language models LLMS sampling-and-voting method agents task difficulty