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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:

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.
bioRxiv (Cold Spring Harbor Laboratory) (2022)
Open Access | Times Cited: 21

Showing 21 citing articles:

Do Large Language Models Know What Humans Know?
Sean Trott, Cameron R. Jones, Tyler H. Chang, et al.
Cognitive Science (2023) Vol. 47, Iss. 7
Open Access | Times Cited: 52
Event Knowledge in Large Language Models: The Gap Between the Impossible and the Unlikely
Carina Kauf, Anna A. Ivanova, Giulia Rambelli, et al.
Cognitive Science (2023) Vol. 47, Iss. 11
Open Access | Times Cited: 32
Lexical-Semantic Content, Not Syntactic Structure, Is the Main Contributor to ANN-Brain Similarity of fMRI Responses in the Language Network
Carina Kauf, Greta Tuckute, Roger Lévy, et al.
Neurobiology of Language (2023) Vol. 5, Iss. 1, pp. 7-42
Open Access | Times Cited: 16
Driving and suppressing the human language network using large language models
Greta Tuckute, Aalok Sathe, Shashank Srikant, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 14
Parallel hierarchical encoding of linguistic representations in the human auditory cortex and recurrent automatic speech recognition systems
Menoua Keshishian, Gavin Mischler, Samuel Thomas, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2025)
Open Access
Correspondence between the layered structure of deep language models and temporal structure of natural language processing in the human brain
Ariel Goldstein, Eric Ham, Samuel A. Nastase, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2022)
Open Access | Times Cited: 16
AI Detection's High False Positive Rates and the Psychological and Material Impacts on Students
Whitney Gegg-Harrison, Claire Quarterman
Advances in educational marketing, administration, and leadership book series (2024), pp. 199-219
Closed Access | Times Cited: 3
Large Language Models: The Need for Nuance in Current Debates and a Pragmatic Perspective on Understanding
Bram van Dijk, Tom Kouwenhoven, Marco Spruit, et al.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2023)
Open Access | Times Cited: 8
Lexical semantic content, not syntactic structure, is the main contributor to ANN-brain similarity of fMRI responses in the language network
Carina Kauf, Greta Tuckute, Roger Lévy, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 7
Surprisal From Language Models Can Predict ERPs in Processing Predicate-Argument Structures Only if Enriched by an Agent Preference Principle
Eva Huber, Sebastian Sauppe, Arrate Isasi-Isasmendi, et al.
Neurobiology of Language (2023) Vol. 5, Iss. 1, pp. 167-200
Open Access | Times Cited: 7
How to Plant Trees in Language Models: Data and Architectural Effects on the Emergence of Syntactic Inductive Biases
Aaron Mueller, Tal Linzen
(2023), pp. 11237-11252
Open Access | Times Cited: 6
Does word knowledge account for the effect of world knowledge on pronoun interpretation?
Cameron R. Jones, Benjamin Bergen
Language and Cognition (2024), pp. 1-32
Open Access | Times Cited: 1
Scale matters: Large language models with billions (rather than millions) of parameters better match neural representations of natural language
Zhuoqiao Hong, Haocheng Wang, Zaid Zada, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access | Times Cited: 1
What language models can tell us about learning adjectives
Megan Gotowski, Forrest Davis
Proceedings of the Linguistic Society of America (2024) Vol. 9, Iss. 1, pp. 5693-5693
Open Access
Prediction of Diabetes Mellitus Using Improved Model of Artificial Neural Network for Early Diagnosis
C. V. Guru Rao, Shaik Balkhis Banu, Dhiraj Kapila
Lecture notes in electrical engineering (2024), pp. 1103-1110
Closed Access
Scale matters: Large language models with billions (rather than millions) of parameters better match neural representations of natural language
Zhuoqiao Hong, Haocheng Wang, Zaid Zada, et al.
(2024)
Open Access
Scale matters: Large language models with billions (rather than millions) of parameters better match neural representations of natural language
Zhuoqiao Hong, Haocheng Wang, Zaid Zada, et al.
(2024)
Open Access
Natural Syntax, Artificial Intelligence and Language Acquisition
William O’Grady, Miseon Lee
Information (2023) Vol. 14, Iss. 7, pp. 418-418
Open Access | Times Cited: 1
Large language models implicitly learn to straighten neural sentence trajectories to construct a predictive representation of natural language
Eghbal A. Hosseini, Evelina Fedorenko
bioRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 1
Shared representations of human actions across vision and language
Diana C. Dima, Sugitha Janarthanan, Jody C. Culham, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 1
CogMemLM: Human-Like Memory Mechanisms Improve Performance and Cognitive Plausibility of LLMs
Lukas Thoma, Ivonne Weyers, Erion Çano, et al.
(2023), pp. 152-157
Open Access | Times Cited: 1
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