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43rd Annual Meeting of the Cognitive Science Society 2021 (10)
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Simple Search
Hits 1 – 10 of 10
1
Are people still smarter than machines? If so, why? ...
43rd Annual Meeting of the Cognitive Science Society 2021
;
McClelland, James
. - : Underline Science Inc., 2021
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2
Using Recurrent Neural Networks to Understand Human Reward Learning ...
43rd Annual Meeting of the Cognitive Science Society 2021
;
Cai, Mingbo
;
Niv, Yael
. - : Underline Science Inc., 2021
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3
Selection, Engagement, & Enhancement: A Framework for Modeling Visual Attention ...
43rd Annual Meeting of the Cognitive Science Society 2021
;
Bello, Paul
;
Bridewell, Will
. - : Underline Science Inc., 2021
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4
Compositional processing emerges in neural networks solving math problems ...
43rd Annual Meeting of the Cognitive Science Society 2021
;
Fernandez, Roland
;
Gao, Jianfeng
. - : Underline Science Inc., 2021
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5
Using playback to investigate multimodal signalling of attractiveness in ring doves (Streptopelia risoria) ...
43rd Annual Meeting of the Cognitive Science Society 2021
;
Biegler, Daniela
;
Canoine, Virginie
. - : Underline Science Inc., 2021
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6
A Layered Bridge from Sound to Meaning: Investigating Cross-linguistic Phonosemantic Correspondences ...
43rd Annual Meeting of the Cognitive Science Society 2021
;
de Varda, Andrea Gregor
;
Strapparava, Carlo
. - : Underline Science Inc., 2021
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7
A Layered Bridge from Sound to Meaning: Investigating Cross-linguistic Phonosemantic Correspondences ...
43rd Annual Meeting of the Cognitive Science Society 2021
;
de Varda, Andrea Gregor
;
Strapparava, Carlo
. - : Underline Science Inc., 2021
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8
Speechless Reader Model: A neurocognitive model for human reading reveals cognitive underpinnings of baboon lexical decision behavior. ...
43rd Annual Meeting of the Cognitive Science Society 2021
;
Gagl, Benjamin
;
Mueller, Jutta
. - : Underline Science Inc., 2021
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9
Cross-language structural priming in recurrent neural network language models ...
43rd Annual Meeting of the Cognitive Science Society 2021
;
Frank, Stefan
. - : Underline Science Inc., 2021
Abstract:
Recurrent neural network (RNN) language models that are trained on large text corpora have shown a remarkable ability to capture properties of human syntactic processing (Linzen & Baroni, 2021). For example, the fact that these models display human-like structural priming effects (Prasad, Van Schijndel, & Linzen, 2019; van Schijndel & Linzen, 2018) suggests that they develop implicit syntactic representations that may not be unlike those of the human language system. A rarely explored question is whether RNNs are also able to simulate aspects of human multilingual sentence processing (Frank, 2021) even though training RNNs on two or more languages simultaneously is technically unproblematic. ...
Keyword:
Cognitive Linguistics
;
Cognitive Neuroscience
;
Cognitive Science
;
Computational Neuroscience
;
Neural Network
;
Semiotics
URL:
https://dx.doi.org/10.48448/naa0-pj67
https://underline.io/lecture/26864-cross-language-structural-priming-in-recurrent-neural-network-language-models
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10
Cross-language structural priming in recurrent neural network language models ...
43rd Annual Meeting of the Cognitive Science Society 2021
;
Frank, Stefan
. - : Underline Science Inc., 2021
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