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All Outputs (12)

(What) Can Deep Learning Contribute to Theoretical Linguistics? (vol 31, pg 617, 2021) (2022)
Journal Article
Dupre, G. (2022). (What) Can Deep Learning Contribute to Theoretical Linguistics? (vol 31, pg 617, 2021). Minds and Machines, 32(1), 11-11. https://doi.org/10.1007/s11023-022-09600-2

Unfortunately, the following article https://doi.org/10.1007/s11023-021-09571-w was by mistake included in another issue but it is part of the Special Issue on Machine learning: Prediction Without Explanation? Gabe Dupre “(What) Can Deep Learning... Read More about (What) Can Deep Learning Contribute to Theoretical Linguistics? (vol 31, pg 617, 2021).

Public language, private language, and subsymbolic theories of mind (2022)
Journal Article
Dupre, G. (2022). Public language, private language, and subsymbolic theories of mind. Mind and Language, 38(2), 394-412. https://doi.org/10.1111/mila.12400

Language has long been a problem-case for subsymbolic theories of mind. The reason for this is obvious: Language seems essentially symbolic. However, recent work has developed a potential solution to this problem, arguing that linguistic symbols are... Read More about Public language, private language, and subsymbolic theories of mind.

Realism and Observation: The View from Generative Grammar (2022)
Journal Article
Dupre. (2022). Realism and Observation: The View from Generative Grammar. Philosophy of Science, 1 - 37. https://doi.org/10.1017/psa.2022.2

Abstract Standard proposals of scientific anti-realism assume that the methodology of a scientific research program can be endorsed without accepting its metaphysical commitments. I argue that the distinction between competence, the rules governing o... Read More about Realism and Observation: The View from Generative Grammar.

(What) Can Deep Learning Contribute to Theoretical Linguistics? (2021)
Journal Article
Dupre. (2021). (What) Can Deep Learning Contribute to Theoretical Linguistics?. Minds and Machines, https://doi.org/10.1007/s11023-021-09571-w

Deep learning (DL) techniques have revolutionised artificial systems’ performance on myriad tasks, from playing Go to medical diagnosis. Recent developments have extended such successes to natural language processing, an area once deemed beyond such... Read More about (What) Can Deep Learning Contribute to Theoretical Linguistics?.

Empiricism, syntax, and ontogeny (2021)
Journal Article
Dupre, G. (2021). Empiricism, syntax, and ontogeny. Philosophical Psychology, 34(7), 1011-1046. https://doi.org/10.1080/09515089.2021.1937591

Generative grammarians typically advocate for a rationalist understanding of language acquisition, according to which the structure of a developed language faculty reflects innate guidance rather than environmental influence. This proposal is develop... Read More about Empiricism, syntax, and ontogeny.

What would it mean for natural language to be the language of thought? (2020)
Journal Article
Dupre. (2020). What would it mean for natural language to be the language of thought?. Linguistics and Philosophy, 773 - 812. https://doi.org/10.1007/s10988-020-09304-9

AbstractTraditional arguments against the identification of the language of thought with natural language assume a picture of natural language which is largely inconsistent with that suggested by contemporary linguistic theory. This has led certain p... Read More about What would it mean for natural language to be the language of thought?.

Idealisation in semantics: truth-conditional semantics for radical contextualists (2020)
Journal Article
Dupre. (2020). Idealisation in semantics: truth-conditional semantics for radical contextualists. Inquiry, 1 - 30. https://doi.org/10.1080/0020174X.2020.1712225

In this paper, I shall provide a novel response to the argument from context-sensitivity against truth-conditional semantics. It is often argued that the contextual influences on truth-conditions outstrip the resources of standard truth-conditional a... Read More about Idealisation in semantics: truth-conditional semantics for radical contextualists.