Large language models (LLMs) have come closest among all models to date to mastering
human language, yet opinions about their linguistic and cognitive capabilities remain split …

Modern deep neural networks achieve impressive performance in engineering applications
that require extensive linguistic skills, such as machine translation. This success has …

Departing from traditional linguistic models, advances in deep learning have resulted in a
new type of predictive (autoregressive) deep language models (DLMs). Using a self …

To what degree can language be acquired from linguistic input alone? This question has
vexed scholars for millennia and is still a major focus of debate in the cognitive science of …

It is one of the central claims of construction grammar that constructions are organized in
some kind of network, commonly referred to as the constructicon. In the classical model of …

Summary Construction Grammar (CxG) has developed into a broad and highly diverse
family of approaches that have in common that they see constructions, ie form-meaning …

Natural language allows us to refer to novel composite concepts by combining expressions
denoting their parts according to systematic rules, a property known as\emph …

A lively research field has recently emerged that uses experimental methods to probe the
linguistic behaviour of modern deep networks. While work in this tradition often reports …

Our ability to comprehend and produce language is one of humans' most impressive skills,
but it is not flawless. We must convey and interpret messages via a noisy channel in ever …

Neural network models are potential tools for improving our understanding of complex brain
functions. To address this goal, these models need to be neurobiologically realistic …