activity
20182021
most citedOn the Predictive Power of Neural Language Models for Human Real-Time Comprehension Behavior

110 citations · 199 across the 5 of their papers we have counts for

collaborators

6 papers

cs.CL2021

Controlled Evaluation of Grammatical Knowledge in Mandarin Chinese Language Models

Yiwen Wang, Jennifer Hu, Roger Levy +1

Prior work has shown that structural supervision helps English language models learn generalizations about syntactic phenomena such as subject-verb agreement. However, it remains u…

cs.CL20212 cited

Scalable pragmatic communication via self-supervision

Jennifer Hu, Roger Levy, Noga Zaslavsky

Models of context-sensitive communication often use the Rational Speech Act framework (RSA; Frank & Goodman, 2012), which formulates listeners and speakers in a cooperative reasoni…

cs.CL2020110 cited

On the Predictive Power of Neural Language Models for Human Real-Time Comprehension Behavior

Ethan Gotlieb Wilcox, Jon Gauthier, Jennifer Hu +2

Human reading behavior is tuned to the statistics of natural language: the time it takes human subjects to read a word can be predicted from estimates of the word's probability in…

cs.CL202027 cited

A Systematic Assessment of Syntactic Generalization in Neural Language Models

Jennifer Hu, Jon Gauthier, Peng Qian +2

While state-of-the-art neural network models continue to achieve lower perplexity scores on language modeling benchmarks, it remains unknown whether optimizing for broad-coverage p…

cs.CL202060 cited

A Rate-Distortion view of human pragmatic reasoning

Noga Zaslavsky, Jennifer Hu, Roger P. Levy

What computational principles underlie human pragmatic reasoning? A prominent approach to pragmatics is the Rational Speech Act (RSA) framework, which formulates pragmatic reasonin…

cs.CL2018

Generating Bilingual Pragmatic Color References

Will Monroe, Jennifer Hu, Andrew Jong +1

Contextual influences on language often exhibit substantial cross-lingual regularities; for example, we are more verbose in situations that require finer distinctions. However, the…