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20182023
most citedOn the Predictive Power of Neural Language Models for Human Real-Time Comprehension Behavior

110 citations · 236 across the 25 of their papers we have counts for

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Showing 2023Show all

5 papers · 1 filter

cs.CL2023

Testing the Predictions of Surprisal Theory in 11 Languages

Ethan Gotlieb Wilcox, Tiago Pimentel, Clara Meister +2

A fundamental result in psycholinguistics is that less predictable words take a longer time to process. One theoretical explanation for this finding is Surprisal Theory (Hale, 2001…

cs.CL2023★ 1 cited

Probing self-supervised speech models for phonetic and phonemic information: a case study in aspiration

Kinan Martin, Jon Gauthier, Canaan Breiss +1

Textless self-supervised speech models have grown in capabilities in recent years, but the nature of the linguistic information they encode has not yet been thoroughly examined. We…

cs.CL2023

The neural dynamics of auditory word recognition and integration

Jon Gauthier, Roger Levy

Listeners recognize and integrate words in rapid and noisy everyday speech by combining expectations about upcoming content with incremental sensory evidence. We present a computat…

cs.CL2023★ 8 cited

Prompting is not a substitute for probability measurements in large language models

Jennifer Hu, Roger Levy

Prompting is now a dominant method for evaluating the linguistic knowledge of large language models (LLMs). While other methods directly read out models' probability distributions…

cs.CL2023★ 1 cited

Expectations over Unspoken Alternatives Predict Pragmatic Inferences

Jennifer Hu, Roger Levy, Judith Degen +1

Scalar inferences (SI) are a signature example of how humans interpret language based on unspoken alternatives. While empirical studies have demonstrated that human SI rates are hi…