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Felix Hao Wang
Felix Hao Wang
Professor, Nanjing Normal University
Dirección de correo verificada de unlv.edu - Página principal
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Año
Word categorization from distributional information: Frames confer more than the sum of their (Bigram) parts
TH Mintz, FH Wang, J Li
Cognitive psychology 75, 1-27, 2014
742014
Successfully learning non-adjacent dependencies in a continuous artificial language stream
FH Wang, J Zevin, TH Mintz
Cognitive Psychology 113, 101223, 2019
172019
Explicit and implicit memory representations in cross-situational word learning
FH Wang
Cognition 205, 104444, 2020
122020
The role of reference in cross-situational word learning
FH Wang, TH Mintz
Cognition 170, 64-75, 2018
122018
Top-down structure influences learning of nonadjacent dependencies in an artificial language.
FH Wang, JD Zevin, TH Mintz
Journal of Experimental Psychology: General 146 (12), 1738, 2017
122017
Learning nonadjacent dependencies embedded in sentences of an artificial language: When learning breaks down.
FH Wang, TH Mintz
Journal of Experimental Psychology: Learning, Memory, and Cognition 44 (4), 604, 2018
112018
Top-down grouping affects adjacent dependency learning
FH Wang, JD Zevin, JC Trueswell, TH Mintz
Psychonomic Bulletin & Review 27, 1052-1058, 2020
102020
Spotting Dalmatians: Children’s ability to discover subordinate-level word meanings cross-situationally
FH Wang, JC Trueswell
Cognitive psychology 114, 101226, 2019
102019
Statistical learning of unfamiliar sounds as trajectories through a perceptual similarity space
FH Wang, EA Hutton, JD Zevin
Cognitive Science 43 (8), e12740, 2019
72019
Being suspicious of suspicious coincidences: The case of learning subordinate word meanings
FH Wang, J Trueswell
Cognition 224, 105028, 2022
52022
Linguistic Priming and Learning Adjacent and Nonadjacent Dependencies in Serial Reaction Time Tasks
FH Wang, E Kaiser
Language Learning 72 (3), 695-727, 2022
12022
Grammatical Bracketing Determines Learning of Non-adjacent Dependencies.
H Wang, JD Zevin, T Mintz
CogSci, 2016
12016
Statistical Structures in Artificial languages Prime Relative Clause Attachment Biases in English.
F Wang, M Menon, E Kaiser
CogSci, 2015
12015
Statistical word segmentation succeeds given the minimal amount of exposure
FH Wang, M Luo, S Wang
Psychonomic bulletin & review, 0
1
The speed of detection vs. segmentation from continuous sequences: Evidence for an anticipation mechanism for detection through a computational model
M Luo, R Cao, FH Wang
eLife 13, 2024
2024
Four‐and six‐year‐old children track a single meaning with both familiar and unfamiliar referents when the referent is clear: More evidence for propose‐but‐verify
FH Wang, M Luo, N Li
Developmental Science 27 (2), e13441, 2024
2024
Perceptual intake explains variability in statistical word segmentation
FH Wang, M Luo, S Wang
Cognition 241, 105612, 2023
2023
Statistical word segmentation succeeds given the minimal amount of exposure
F Hao Wang, M Luo, S Wang
Psychonomic Bulletin & Review, 1-9, 2023
2023
Iambic Bias in Parsing Syllable Sequences by English Speakers.
R Budnick, F Wang
CogSci, 2018
2018
A New Model of Statistical Learning: Trajectories Through Perceptual Similarity Space.
EA Hutton, FH Wang, JD Zevin
CogSci, 2017
2017
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Artículos 1–20