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 …

Researchers agree that comprehenders regularly predict upcoming language, but they do
not always agree on what prediction is (and how to differentiate it from integration) or what …

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

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

Recent research in artificial intelligence and machine learning has largely emphasized
general-purpose learning and ever-larger training sets and more and more compute. In …

Cognitive linguists and psychologists have often argued that language is best understood as
an association network; however while the network view of language has had a significant …

In image captioning, the typical attention mechanisms are arduous to identify the equivalent
visual signals especially when predicting highly abstract words. This phenomenon is known …

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 …

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' …

In this paper we address the question of how to render sequence-level networks better at
handling structured input. We propose a machine reading simulator which processes text …