91 citations · 189 across the 25 of their papers we have counts for
5 papers · 1 filter
A fine-grained comparison of pragmatic language understanding in humans and language models
Jennifer Hu, Sammy Floyd, Olessia Jouravlev +2
Pragmatics and non-literal language understanding are essential to human communication, and present a long-standing challenge for artificial language models. We perform a fine-grai…
Event knowledge in large language models: the gap between the impossible and the unlikely
Carina Kauf, Anna A. Ivanova, Giulia Rambelli +5
Word co-occurrence patterns in language corpora contain a surprising amount of conceptual knowledge. Large language models (LLMs), trained to predict words in context, leverage the…
Beyond linear regression: mapping models in cognitive neuroscience should align with research goals
Anna A. Ivanova, Martin Schrimpf, Stefano Anzellotti +3
Many cognitive neuroscience studies use large feature sets to predict and interpret brain activity patterns. Feature sets take many forms, from human stimulus annotations to repres…
Interpretability of artificial neural network models in artificial Intelligence vs. neuroscience
Kohitij Kar, Simon Kornblith, Evelina Fedorenko
Computationally explicit hypotheses of brain function derived from machine learning (ML)-based models have recently revolutionized neuroscience. Despite the unprecedented ability o…
Grammatical cues to subjecthood are redundant in a majority of simple clauses across languages
Kyle Mahowald, Evgeniia Diachek, Edward Gibson +2
Grammatical cues are sometimes redundant with word meanings in natural language. For instance, English word order rules constrain the word order of a sentence like "The dog chewed…