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  Clarifying status of DNNs as models of human vision

Bowers, J. S., Malhotra, G., Dujmović, M., Montero, M. L., Tsvetkov, C., Biscione, V., et al. (2023). Clarifying status of DNNs as models of human vision. Behavioral and Brain Sciences, 46: e415. doi:10.1017/S0140525X23002777.

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Item Permalink: https://hdl.handle.net/21.11116/0000-000E-08C1-F Version Permalink: https://hdl.handle.net/21.11116/0000-000E-08C2-E
Genre: Journal Article

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 Creators:
Bowers, Jeffrey S., Author
Malhotra, Gaurav, Author
Dujmović, Marin, Author
Montero, Milton L., Author
Tsvetkov, Christian, Author
Biscione, Valerio, Author
Puebla, Guillermo, Author
Adolfi, Federico1, 2, Author
Hummel, John E., Author
Heaton, Rachel F., Author
Evans, Benjamin D., Author
Mitchell, Jeffrey, Author
Blything, Ryan, Author
Affiliations:
1Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Max Planck Society, Deutschordenstr. 46, 60528 Frankfurt, DE, ou_2074314              
2Poeppel Lab, Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Max Planck Society, Deutschordenstraße 46, 60528 Frankfurt, DE, ou_3381225              

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 Abstract: On several key issues we agree with the commentators. Perhaps most importantly, everyone seems to agree that psychology has an important role to play in building better models of human vision, and (most) everyone agrees (including us) that deep neural networks (DNNs) will play an important role in modelling human vision going forward. But there are also disagreements about what models are for, how DNN–human correspondences should be evaluated, the value of alternative modelling approaches, and impact of marketing hype in the literature. In our view, these latter issues are contributing to many unjustified claims regarding DNN–human correspondences in vision and other domains of cognition. We explore all these issues in this response.

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 Dates: 2023-12-062023
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1017/S0140525X23002777
 Degree: -

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Title: Behavioral and Brain Sciences
Source Genre: Journal
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Pages: - Volume / Issue: 46 Sequence Number: e415 Start / End Page: - Identifier: ISSN: 0140-525X
ISSN: 1469-1825