Abstract Word co-occurrence patterns in language corpora contain a surprising amount of conceptual knowledge. Large language models (LLMs), trained to predict words in context, leverage these patterns to achieve impressive performance on diverse semantic tasks requiring world knowledge. An important but understudied question about LLMs’ semantic abilities is whether they acquire generalized knowledge of common […]

Abstract Iconicity refers to a resemblance between word form and meaning. Previous work has shown that iconic words are learned earlier and processed faster. Here, we examined whether iconic words are recognized better on a recognition memory task. We also manipulated the level at which items were encoded—with a focus on either their meaning or […]

This paper proposes a neural network model that estimates the rotation angle of unknown objects from RGB images using an approach inspired by biological neural circuits. The proposed model embeds the understanding of rotational transformations into its architecture, in a way inspired by how rotation is represented in the ellipsoid body of Drosophila. To effectively […]