AI-AI偏见矩阵重分析：未发现模型偏好自身生成文本的证据
原标题：A Shared Taste for Model-Written Text: The Generator-by-Selector Matrices of "AI-AI Bias" Show No Detectable Own-Model Premium
AI 摘要
该研究重新分析Laurito等（PNAS 2025）的公开数据，检验大语言模型作为选择者时是否偏好自己生成的文本。通过重建三个5×5生成者-选择者矩阵并拟合双向固定效应模型，发现自身模型溢价在三个数据集上均不显著，合并数据中95%置信区间包含零。研究确认了原论文的主要结论——模型普遍偏好模型撰写的文本，但未发现模型识别并偏爱自身文风的证据。
正文节选
A Shared Taste for Model-Written Text: The Generator-by-Selector Matrices of “AI–AI Bias” Show No Detectable Own-Model Premium Abstract Laurito et al. (PNAS 2025) showed that large language models choosing between two descriptions of the same product, paper or film prefer the description written by a language model over the one written by a person, by a wide margin over what human judges do. Their design crosses five generators with the same five models as selectors, which permits a second quest