Bridging the meaning gap: A computational approach to semantic variation

弥合意义差距：语义变异的计算方法

• 批准号: DP240101873
• 负责人: Prof Andrew Perfors
• 金额: $ 46.97万
• 依托单位: The University of Melbourne
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Projects
• 财政年份: 2024
• 资助国家: 澳大利亚
• 起止时间: 2024-01-01 至 2027-12-31
• 项目状态: 未结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DP240101873
• 关键词: Bridging; meaning; gap; computational; approach

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.

该项目旨在创建并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) 衡量个体之间词义和语言体验的细微差别； (2) 开发包含这种变化的计算模型； (3) 评估模型捕捉与政治立场、性别和文化相关的行为和认知差异的程度。这将增进我们对个体差异的本质和起源的理解，并改善人工智能系统对代表性不足群体的校准。这些进步将支持健康、国内安全和抵御错误信息的最终应用成果。