Performance of single-agent and multi-agent language models in Spanish language medical competency exams

Abstract

Multi-agent strategies, particularly MDAGENTS, significantly enhance GPT-4o's performance on Spanish-language medical exams, leveraging collaboration to improve diagnostic accuracy. However, simpler single-agent strategies are sufficient to address many questions, high-lighting that only a fraction of standardized medical exams require sophisticated reasoning or multi-agent interaction. These findings suggest potential for LLMs as efficient and scalable tools in Spanish-speaking healthcare, though computational optimization remains a key area for future research.

Ähnliche Arbeiten