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 …

Natural language processing employs computational techniques for the purpose of learning,
understanding, and producing human language content. Early computational approaches to …

Language models (LMs) are becoming the foundation for almost all major language
technologies, but their capabilities, limitations, and risks are not well understood. We present …

A brain–computer interface that decodes continuous language from non-invasive recordings
would have many scientific and practical applications. Currently, however, non-invasive …

AI is undergoing a paradigm shift with the rise of models (eg, BERT, DALL-E, GPT-3) that are
trained on broad data at scale and are adaptable to a wide range of downstream tasks. We …

The widespread adoption of large language models (LLMs) makes it important to recognize
their strengths and limitations. We argue that to develop a holistic understanding of these …

This work presents a linguistic analysis into why larger Transformer-based pre-trained
language models with more parameters and lower perplexity nonetheless yield surprisal …

The neuroscience of perception has recently been revolutionized with an integrative
modeling approach in which computation, brain function, and behavior are linked across …

Abstract Language models (LMs) like GPT‐3, PaLM, and ChatGPT are the foundation for
almost all major language technologies, but their capabilities, limitations, and risks are not …

During real-time language comprehension, our minds rapidly decode complex meanings
from sequences of words. The difficulty of doing so is known to be related to words' …