Article

Predicting visual working memory errors with a priori measures of representational geometry from human and artificial systems

2026-06-02

Abstract excerpt

<p>A longstanding question in cognitive science is whether the structure of mental representations — deriving from perceptual and semantic knowledge — can be used to generate a priori quantitative predictions of the specific errors people make in memory. Using both human similarity judgments and an ensemble of modern pretrained deep neural networks trained for general visual tasks, with no memory-task or face-iden...

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Literature Corpus work: f78fe58f-f861-5e32-b5dd-0cbf79080eec
DOI: 10.31234/osf.io/k3xu6_v1

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