Bridging the meaning gap: A computational approach to semantic variation

该项目旨在创建和验证一类新的大型语言模型，以捕获并部分解释人与人之间的语义差异。我们将(1)衡量不同个体在词义和语言体验上的细微差异；(2)开发包含这种差异的计算模型；以及(3)评估这些模型在多大程度上捕捉到与政治派系、性别和文化相关的行为和认知差异。这将促进我们对个体差异的性质和根源的理解，并改进对代表不足群体的人工智能系统的校准。这些进展将支持在卫生、国内安全和抵御错误信息方面的最终应用成果。

This project aims to create and validate a new class of large language models that capture and partially explain semantic variation between people. We will (1) measure nuanced differences in word meaning and linguistic experience across individuals; (2) develop computational models that incorporate this variation; and (3) evaluate the extent to which the models capture behavioural and cognitive differences related to political affiliation, gender, and culture. This will advance our understanding of the nature and origin of individual differences as well as improve the calibration of AI systems for under-represented groups. These advances will support eventual applied outcomes in health, domestic security, and resilience to misinformation.