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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

The effect of word predictability on reading time is logarithmic
Nathaniel J. Smith, Roger Lévy
Cognition (2013) Vol. 128, Iss. 3, pp. 302-319
Open Access | Times Cited: 647

Showing 26-50 of 647 citing articles:

The Domain-General Multiple Demand (MD) Network Does Not Support Core Aspects of Language Comprehension: A Large-Scale fMRI Investigation
Evgeniia Diachek, Idan Blank, Matthew Siegelman, et al.
Journal of Neuroscience (2020) Vol. 40, Iss. 23, pp. 4536-4550
Open Access | Times Cited: 146
Semantic projection recovers rich human knowledge of multiple object features from word embeddings
Gabriel Grand, Idan Blank, Francisco Pereira, et al.
Nature Human Behaviour (2022) Vol. 6, Iss. 7, pp. 975-987
Open Access | Times Cited: 121
Why Does Surprisal From Larger Transformer-Based Language Models Provide a Poorer Fit to Human Reading Times?
Byung-Doh Oh, William Schuler
Transactions of the Association for Computational Linguistics (2023) Vol. 11, pp. 336-350
Open Access | Times Cited: 52
Driving and suppressing the human language network using large language models
Greta Tuckute, Aalok Sathe, Shashank Srikant, et al.
Nature Human Behaviour (2024) Vol. 8, Iss. 3, pp. 544-561
Open Access | Times Cited: 30
Large-scale evidence for logarithmic effects of word predictability on reading time
Cory Shain, Clara Meister, Tiago Pimentel, et al.
Proceedings of the National Academy of Sciences (2024) Vol. 121, Iss. 10
Open Access | Times Cited: 26
Artificial Neural Network Language Models Predict Human Brain Responses to Language Even After a Developmentally Realistic Amount of Training
Eghbal A. Hosseini, Martin Schrimpf, Yian Zhang, et al.
Neurobiology of Language (2024) Vol. 5, Iss. 1, pp. 43-63
Open Access | Times Cited: 17
Pre‐Processing in Sentence Comprehension: Sensitivity to Likely Upcoming Meaning and Structure
Katherine A. DeLong, Melissa Troyer, Marta Kutas
Language and Linguistics Compass (2014) Vol. 8, Iss. 12, pp. 631-645
Open Access | Times Cited: 155
Language structure in the brain: A fixation-related fMRI study of syntactic surprisal in reading
John M. Henderson, Wonil Choi, Matthew W. Lowder, et al.
NeuroImage (2016) Vol. 132, pp. 293-300
Open Access | Times Cited: 154
Pragmatic reasoning through semantic inference
Leon Bergen, Roger Lévy, Noah D. Goodman
Semantics and Pragmatics (2016) Vol. 9
Open Access | Times Cited: 154
Regression‐based estimation of ERP waveforms: I. The rERP framework
Nathaniel J. Smith, Marta Kutas
Psychophysiology (2014) Vol. 52, Iss. 2, pp. 157-168
Open Access | Times Cited: 147
Semantic Context Enhances the Early Auditory Encoding of Natural Speech
Michael P. Broderick, Andrew Anderson, Edmund C. Lalor
Journal of Neuroscience (2019) Vol. 39, Iss. 38, pp. 7564-7575
Open Access | Times Cited: 140
The syntactic complexity of Russian relative clauses
Roger Lévy, Evelina Fedorenko, Edward Gibson
Journal of Memory and Language (2013) Vol. 69, Iss. 4, pp. 461-495
Open Access | Times Cited: 139
Uncertainty and Expectation in Sentence Processing: Evidence From Subcategorization Distributions
Tal Linzen, T. Florian Jaeger
Cognitive Science (2015) Vol. 40, Iss. 6, pp. 1382-1411
Open Access | Times Cited: 131
A Systematic Assessment of Syntactic Generalization in Neural Language Models
Jennifer Hu, Jon Gauthier, Peng Qian, et al.
(2020)
Open Access | Times Cited: 130
Goals and strategies influence lexical prediction during sentence comprehension
Trevor Brothers, Tamara Y. Swaab, Matthew J. Traxler
Journal of Memory and Language (2016) Vol. 93, pp. 203-216
Open Access | Times Cited: 127
Combined eye tracking and fMRI reveals neural basis of linguistic predictions during sentence comprehension
Corinna Bonhage, Jutta L. Mueller, Angela D. Friederici, et al.
Cortex (2015) Vol. 68, pp. 33-47
Closed Access | Times Cited: 124
Lossy‐Context Surprisal: An Information‐Theoretic Model of Memory Effects in Sentence Processing
Richard Futrell, Edward Gibson, Roger Lévy
Cognitive Science (2020) Vol. 44, Iss. 3
Open Access | Times Cited: 123
Language Processing as Cue Integration: Grounding the Psychology of Language in Perception and Neurophysiology
Andrea E. Martin
Frontiers in Psychology (2016) Vol. 7
Open Access | Times Cited: 120
The Provo Corpus: A large eye-tracking corpus with predictability norms
Steven G. Luke, Kiel Christianson
Behavior Research Methods (2017) Vol. 50, Iss. 2, pp. 826-833
Open Access | Times Cited: 120
Cortical Tracking of Surprisal during Continuous Speech Comprehension
Hugo Weissbart, Katerina Danae Kandylaki, Tobias Reichenbach
Journal of Cognitive Neuroscience (2019) Vol. 32, Iss. 1, pp. 155-166
Open Access | Times Cited: 117
The Oxford Handbook of Experimental Semantics and Pragmatics

Oxford University Press eBooks (2019)
Closed Access | Times Cited: 113
Word predictability and semantic similarity show distinct patterns of brain activity during language comprehension
Stefan L. Frank, Roel M. Willems
Language Cognition and Neuroscience (2017) Vol. 32, Iss. 9, pp. 1192-1203
Open Access | Times Cited: 112
Prediction, Information Structure, and Good-Enough Language Processing
Fernanda Ferreira, Matthew W. Lowder
˜The œPsychology of learning and motivation/˜The œpsychology of learning and motivation (2016), pp. 217-247
Closed Access | Times Cited: 111
Integration and Prediction in Language Processing: A Synthesis of Old and New
Fernanda Ferreira, Suphasiree Chantavarin
Current Directions in Psychological Science (2018) Vol. 27, Iss. 6, pp. 443-448
Open Access | Times Cited: 111
Trends in syntactic parsing: anticipation, Bayesian estimation, and good-enough parsing
Matthew J. Traxler
Trends in Cognitive Sciences (2014) Vol. 18, Iss. 11, pp. 605-611
Open Access | Times Cited: 110

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