In this paper we carry out an extensive comparison of many off-the-shelf distributed semantic
vectors representations of words, for the purpose of making predictions about behavioural …

Previous research has suggested that distributional learning mechanisms may contribute to
the acquisition of semantic knowledge. However, distributional learning mechanisms …

Circular convolution and random permutation have each been proposed as neurally
plausible binding operators capable of encoding sequential information in semantic …

One proposal that can explain the remarkable pace of word learning in young children is
that they leverage the language-internal distributional similarity of familiar and novel words …

The diversity of a word's contexts affects its acquisition andprocessing. Can differences
between word types such asmonosemes (unambiguous words), polysemes (multiple …

There has been a recent boom in research relating semantic space computational models to
fMRI data, in an effort to better understand how the brain represents semantic information. In …

Distributional models (such as neural network language mod-els) have been successfully
used to model a wide range of lin-guistic semantic behaviors. However, they lack a way to …

Human free association (FA) norms are believed to reflect thestrength of links between
words in the lexicon of an averagespeaker. Large-scale FA norms are commonly used as a …

The article makes a framework for reviews of some works of empirical and experimental
research that do not use imaging but contrastive analysis or tests naming and lexical …

What is the nature of the relationship between Knowledge and Language How does
knowledge representation interact with language use? The critical role of world knowledge …