Results 211 to 220 of about 89,998 (313)

Computational Psycholinguistics

Computational Linguistics, 2020
Kaplan, Ronald M.
doaj   +1 more source

Publisher Correction: Expression and regulation of SETBP1 in the song system of male zebra finches (Taeniopygia guttata) during singing. [PDF]

Sci Rep
Grönberg DJ, de Carvalho SLP, Dernerova N, Norton P, Wong MM, Mendoza E.   +5 more
europepmc   +1 more source

Book Review: Stoyanova, J. (2021) Problemi na psiholingvistikata [Problems of Psycholinguistics]. Sofia University Press. pp. 576, ISBN 9786197433517.

, 2023
Hristo Kyuchukov
openalex   +2 more sources

Beyond the Lab: Cognitive Neuroscience in Real‐World Contexts

WIREs Cognitive Science, Volume 17, Issue 2, March/April 2026.
Cognitive neuroscience often assumes that using laboratory animals, model species, and digital simulations enables generalizations from lab to wild, from animals to humans, and from virtual to physical. We challenge these assumptions and call for refining ecological validity along three dimensions: subject phenotype, task naturalness, and environmental
Stephan P. Kaufhold, Mia Borzello, Federico Rossano, David Kirsh   +3 more
wiley   +1 more source

Examining Chat GPT with nonwords and machine psycholinguistic techniques. [PDF]

PLoS One
Vitevitch MS.
europepmc   +1 more source

Ontological polyglossia: the art of communicating in opacity* Polyglossie ontologique : l'art de communiquer dans l'opacité

Journal of the Royal Anthropological Institute, Volume 32, Issue 1, Page 293-312, March 2026.
What do communicating with a baby, with an animal, and with an ancestor have in common? In all three cases, people engage in opaque communication that is far from the standard psycholinguistic model of transparent interaction based on shared intentionality.
Charles Stépanoff
wiley   +1 more source

Glyph norming: Human and computational measurements of shape angularity in writing systems. [PDF]

Behav Res Methods
Porto A, Huckle N, Basalyga A, Santiago J, Kranjec A.   +4 more
europepmc   +1 more source

Evidence Against Syntactic Encapsulation in Large Language Models

Cognitive Science, Volume 50, Issue 3, March 2026.
Abstract Transformer‐based large language models (LLMs) have recently demonstrated exceptional performance in a variety of linguistic tasks. LLMs primarily combine information across words in a sentence using the attention mechanism, implemented by “attention heads:” these components assign numerical weights linking different words in the input to one ...
Thomas A. McGee, Yiyang Zhang, Idan A. Blank   +2 more
wiley   +1 more source

The German Auditory and Image (GAudI) vocabulary test: A new German receptive vocabulary test and its relationships to other tests measuring linguistic experience. [PDF]

PLoS One
Bethke S, Meyer AS, Hintz F.
europepmc   +1 more source

Formulaic Language in Native and Second Language Speakers: Psycholinguistics, Corpus Linguistics, and TESOL

, 2008
N. Ellis, Rita Simpson-Vlach, C. Maynard
semanticscholar   +1 more source