This is the Algonauts 2023 submission report for team "BlobGPT". Our model consists of a multi-subject linear encoding head attached to a pretrained trunk model. The multi-subject head consists of three components: (1) a shared multi-layer feature projection, (2) shared plus subject-specific low-dimension linear transformations, and (3) a shared PCA fMRI embedding. In this report, we explain these components in more detail and present some experimental results. Our code is available at https://github.com/cmi-dair/algonauts23.

翻译：这是2023年Algonauts竞赛中“BlobGPT”队伍的技术报告。我们的模型由一个多被试线性编码头连接至预训练主干模型构成。该多被试编码头包含三个组件：(1)共享的多层特征投影层；(2)共享与个体特定低维线性变换的组合模块；以及(3)共享的主成分分析fMRI嵌入模块。本报告将详细阐述这些组件的工作原理，并展示部分实验结果。相关代码已开源在 https://github.com/cmi-dair/algonauts23。