Adult semantic memory has been traditionally conceptualized as a relatively static memory
system that consists of knowledge about the world, concepts, and symbols. Considerable …

Models that represent meaning as high-dimensional numerical vectors—such as latent
semantic analysis (LSA), hyperspace analogue to language (HAL), bound encoding of the …

While the incipient internet was largely text-based, the modern digital world is becoming
increasingly multi-modal. Here, we examine multi-modal classification where one modality is …

Recent decades have ushered in tremendous progress in understanding the neural basis of
language. Most of our current knowledge on language and the brain, however, is derived …

Multi-modal semantics has relied on feature norms or raw image data for perceptual input. In
this paper we examine grounding semantic representations in raw auditory data, using …

Abstract Formal Semantics and Distributional Semantics are two very influential semantic
frameworks in Computational Linguistics. Formal Semantics is based on a symbolic tradition …

Experimental design and computational modelling across the cognitive sciences often rely
on measures of semantic similarity between concepts. Traditional measures of semantic …

Meaning has been called the" holy grail" of a variety of scientific disciplines, ranging from
linguistics to philosophy, psychology and the neurosciences. The field of Artifical Intelligence …

Previous studies found that an automatic meaning-composition process affects the
processing of morphologically complex words, and related this operation to conceptual …

Multimodal models have been proven to outperform text-based models on learning semantic
word representations. According to psycholinguistic theory, there is a graphical relationship …