TransDis：基于Transformer语言模型的中文发散思维自动评估方法
Automatic Assessment of Divergent Thinking in Chinese Language with TransDis: A Transformer-Based Language Model Approach
AI总结：
针对中文创造力评估缺失，提出基于Transformer的TransDis系统，能有效评估AUT任务的原创性与灵活性，效度与人类评分相当，并开放多语言平台。
摘要：
语言模型在自动创造力评估中越来越受欢迎，通过生成语义距离来客观衡量创意质量。然而，目前缺乏用于评估中文创意想法的自动评估系统。为弥补这一空白，我们开发了TransDis，一个使用基于Transformer的语言模型的评分系统，能够为中文替代用途任务（AUT）的回答提供有效的原创性（质量）和灵活性（多样性）评分。研究1表明，由三个基于Transformer的模型组成的潜在模型评分原创性因子，能强烈预测人类对原创性的评分，且模型评分的灵活性与人类评分的灵活性也高度相关。效标效度分析显示，模型评分的原创性和灵活性与其他创造力测量呈正相关，展现出与人类评分相似的效度。研究2和研究3表明，TransDis能有效区分被指示提供创造性用途与普通用途的参与者（研究2），以及被指示以灵活方式与持续方式生成想法的参与者（研究3）。我们的发现表明，TransDis可以成为衡量中文语言中想法原创性和灵活性的可靠且低成本工具，可能为其他语言的自动创造力评估铺平道路。我们提供了一个开放平台，用于计算中文及50多种其他语言的AUT回答的原创性和灵活性（https://osf.io/59jv2/）。
英文摘要：
Language models have been increasingly popular for automatic creativity assessment, generating semantic distances to objectively measure the quality of creative ideas. However, there is currently a lack of an automatic assessment system for evaluating creative ideas in the Chinese language. To address this gap, we developed TransDis, a scoring system using transformer-based language models, capable of providing valid originality (quality) and flexibility (variety) scores for Alternative Uses Task (AUT) responses in Chinese. Study 1 demonstrated that the latent model-rated originality factor, comprised of three transformer-based models, strongly predicted human originality ratings, and the model-rated flexibility strongly correlated with human flexibility ratings as well. Criterion validity analyses indicated that model-rated originality and flexibility positively correlated to other creativity measures, demonstrating similar validity to human ratings. Study 2 & 3 showed that TransDis effectively distinguished participants instructed to provide creative vs. common uses (Study 2) and participants instructed to generate ideas in a flexible vs. persistent way (Study 3). Our findings suggest that TransDis can be a reliable and low-cost tool for measuring idea originality and flexibility in Chinese language, potentially paving the way for automatic creativity assessment in other languages. We offer an open platform to compute originality and flexibility for AUT responses in Chinese and over 50 other languages (https://osf.io/59jv2/).
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
