In this episode, we discuss More Agents Is All You Need by Junyou Li, Qin Zhang, Yangbin Yu, Qiang Fu, Deheng Ye. The study demonstrates that the effectiveness of large language models (LLMs) improves when more instances of the model (agents) are used in a simple sampling-and-voting technique. This technique can be combined with other advanced methods to further improve LLM performance, especially for more challenging tasks. Extensive experimentation across various benchmarks confirms these results, and the researchers have made their code accessible to the public.
