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最先进的LLM在KDLE上的比较表现:2025年基准研究

Taejun Kim¹, Bong Chul Kim¹

¹Department of Oral and Maxillofacial Surgery, Daejeon Dental Hospital, Wonkwang University College of Dentistry, Daejeon, Republic of Korea.

International dental journal

|February 28, 2026

概括

四个先进的大型语言模型 (LLM) 在韩国牙科执照考试 (KDLE) 上表现出色,其中三个接近人类能力. 然而,视觉解释方面的局限性仍然存在,这表明LLMs应该补充,而不是取代牙科教育中的人类专业知识.

科学领域:

人工智能在牙科中的应用
医疗教育技术技术医学教育
牙科诊断牙科诊断牙科诊断

背景情况:

大型语言模型 (LLM) 正在迅速发展.
在专业的专业考试中评估LLM能力至关重要.
韩国牙科执照考试 (KDLE) 为牙科知识和推理提供了一个标准化的基准.

研究的目的:

评估KDLE四个领先的LLM的诊断和推理能力.
确定这些LLM作为牙科补充教育工具的潜力.
为了比较不同LLM在高风险的牙科检查中的表现.

主要方法:

四个LLM (ChatGPT-4o,Claude-4 Opus,Gemini 2.5 Pro,DeepSeek-V3) 在642个官方KDLE问题上进行了测试,时间从2024-2025年开始.
通过整体准确性,模式 (文本与图像) 和特定主题分析来评估性能.
为了进行严格的比较,使用了包括科克兰的Q和麦克内马尔的测试在内的统计测试.

主要成果:

所有评估的LLM都超过了KDLE的合格门.
聊天GPT-4o,Claude-4 Opus和Gemini 2.5 Pro的分数与人类受试者的分数相当或超过.
在基于文字的问题上,LLM的表现比基于图像的问题更好,并且在牙科科目中显示出差异性.

结论:

当代LLM在牙医执照考试中表现出显著的诊断和推理能力.
在四个LLM中,有三个显示出接近人类的性能水平.
视觉解释和临床推理的局限性需要持续的人类监督,将LLM定位为补充教育辅助工具.

关键词:

人工智能的人工智能是人工智能.牙科牙科是指牙科的专业.考试问题考试问题大型语言模型.

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