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 …

Artificial neural networks (ANNs) inspired by biology are beginning to be widely used to
model behavioural and neural data, an approach we call 'neuroconnectionism'. ANNs have …

Considerable progress has recently been made in natural language processing: deep
learning algorithms are increasingly able to generate, summarize, translate and classify …

Why our use of language is highly creative yet also constrained We use words and phrases
creatively to express ourselves in ever-changing contexts, readily extending language …

Cognitive science applies diverse tools and perspectives to study human language.
Recently, an exciting body of work has examined linguistic phenomena through the lens of …

This two-part comprehensive survey is devoted to a computing framework most commonly
known under the names Hyperdimensional Computing and Vector Symbolic Architectures …

Recent progress in artificial intelligence has renewed interest in building systems that learn
and think like people. Many advances have come from using deep neural networks trained …

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

Understanding language requires more than the use of fixed conventions and more than
decoding combinatorial structure. Instead, comprehenders make exquisitely sensitive …

The most critical attribute of human language is its unbounded combinatorial nature: smaller
elements can be combined into larger structures on the basis of a grammatical system …