Models that represent meaning as high-dimensional numerical vectors—such as latent semantic analysis (LSA), hyperspace analogue to language (HAL), bound encoding of the aggregate language environment (BEAGLE), topic models, global vectors (GloVe), and word2vec—have been introduced as extremely powerful machine-learning proxies for human semantic representations and have seen an explosive rise in popularity over the past 2 decades. However, despite their considerable advancements and spread in the cognitive sciences, one can observe problems associated with the adequate presentation and understanding of some of their features. Indeed, when these models are examined from a cognitive perspective, a number of unfounded arguments tend to appear in the psychological literature. In this article, we review the most common of these arguments and discuss (a) what exactly these models represent at the implementational level and their plausibility as a cognitive theory, (b) how they deal with various aspects of meaning such as polysemy or compositionality, and (c) how they relate to the debate on embodied and grounded cognition. We identify common misconceptions that arise as a result of incomplete descriptions, outdated arguments, and unclear distinctions between theory and implementation of the models. We clarify and amend these points to provide a theoretical basis for future research and discussions on vector models of semantic representation.

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The present study examined whether traveling through serially-ordered verbal memories exploits overt visuospatial attentional resources. In a three-phase behavioral study, five single-digits were presented sequentially at one spatial location in phase 1, while recognition and verbal recall were tested in phases 2 and 3, respectively. Participants' spontaneous eye movements were registered along with the verbal responses. Results showed that the search and the retrieval of serially-ordered information were mediated by spontaneous ocular movements. Specifically, recognizing middle items of the memorized sequence required longer inspection times and, importantly, a greater involvement of overt attentional resources, than recognizing the serially first-presented item and, to a lesser extent, the last-presented item. Moreover, serial order was found to be spatially encoded from left-to-right, as eye position during vocal responses deviated the more to the right, the later the serial position of the retrieved item in the sequence. These findings suggest that overt spatial attention mediates the scanning of serial order representation.

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