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大型语言模型能够淡化他们的认知能力,以适应他们模拟的人格

Jiří Milička¹, Anna Marklová², Klára VanSlambrouck³

¹Institute of the Czech National Corpus, Faculty of Arts, Charles University, Prague, Czech Republic.

|March 13, 2024

概括

像GPT-4这样的大型语言模型 (LLM) 可以在解决错误信念任务时模拟类似儿童的认知发展和语言技能. 这些模型显示了与人类儿童相似的发育模式,证明了他们调整表现的能力.

科学领域:

认知科学认知科学
发展心理学发展心理学
人工智能的人工智能

背景情况:

大型语言模型 (LLM) 是越来越复杂的AI系统.
了解LLM在模拟人类认知发展方面的能力至关重要.
儿童发育研究为评估认知和语言进展提供了一个基准.

研究的目的:

调查LLM (GPT-3.5-turbo和GPT-4) 模拟儿童认知和语言发展的能力.
评估不同年龄模拟 (1-6岁) 的错误信念任务 (位置变化和意想不到的内容) 的LLM绩效.
分析各种提示策略对模拟准确性的影响.

主要方法:

模拟了1296名1-6岁儿童使用GPT-3.5-turbo和GPT-4.
采用了三种提示类型:零射击,链式思维和通过体进行启动.
评估了响应正确性和语言复杂性 (发言长度,科尔摩戈罗夫复杂性).

主要成果:

两种模型都显示,随着模拟年龄的增加,响应正确性和语言复杂性都在增加,反映了人类儿童的发展.
GPT-4显示与发育曲线更接近,但在特定提示时表现出高精度.
提示类型和模型选择显著影响了发展模式;任务类型也起到了作用.

结论:

实际上,LLM可以有效地降低其模拟特定发育阶段和认知技能的能力.
这些发现强调了LLMs作为发展心理学研究工具的潜力.
法学士模拟提供了对认知和语言发展机制的见解.

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