15 found
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  1.  22
    The Communicative Function of Ambiguity in Language.Steven T. Piantadosi, Harry Tily & Edward Gibson - 2012 - Cognition 122 (3):280-291.
  2.  20
    The Logical Primitives of Thought: Empirical Foundations for Compositional Cognitive Models.Steven T. Piantadosi, Joshua B. Tenenbaum & Noah D. Goodman - 2016 - Psychological Review 123 (4):392-424.
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  3.  45
    Bootstrapping in a Language of Thought: A Formal Model of Numerical Concept Learning.Steven T. Piantadosi, Joshua B. Tenenbaum & Noah D. Goodman - 2012 - Cognition 123 (2):199-217.
  4.  41
    Info/Information Theory: Speakers Choose Shorter Words in Predictive Contexts.Kyle Mahowald, Evelina Fedorenko, Steven T. Piantadosi & Edward Gibson - 2013 - Cognition 126 (2):313-318.
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  5.  9
    How Efficiency Shapes Human Language.Edward Gibson, Richard Futrell, Steven T. Piantadosi, Isabelle Dautriche, Kyle Mahowald, Leon Bergen & Roger Levy - 2019 - Trends in Cognitive Sciences 23 (12):1087.
  6.  25
    Wordform Similarity Increases With Semantic Similarity: An Analysis of 100 Languages.Isabelle Dautriche, Kyle Mahowald, Edward Gibson & Steven T. Piantadosi - 2017 - Cognitive Science:2149-2169.
    Although the mapping between form and meaning is often regarded as arbitrary, there are in fact well-known constraints on words which are the result of functional pressures associated with language use and its acquisition. In particular, languages have been shown to encode meaning distinctions in their sound properties, which may be important for language learning. Here, we investigate the relationship between semantic distance and phonological distance in the large-scale structure of the lexicon. We show evidence in 100 languages from a (...)
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  7.  13
    Words Cluster Phonetically Beyond Phonotactic Regularities.Isabelle Dautriche, Kyle Mahowald, Edward Gibson, Anne Christophe & Steven T. Piantadosi - 2017 - Cognition 163:128-145.
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  8.  6
    The Child as Hacker.Joshua S. Rule, Joshua B. Tenenbaum & Steven T. Piantadosi - 2020 - Trends in Cognitive Sciences 24 (11):900-915.
  9.  23
    Word Forms Are Structured for Efficient Use.Kyle Mahowald, Isabelle Dautriche, Edward Gibson & Steven T. Piantadosi - 2018 - Cognitive Science 42 (8):3116-3134.
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  10.  15
    The Computational Origin of Representation.Steven T. Piantadosi - 2021 - Minds and Machines 31 (1):1-58.
    Each of our theories of mental representation provides some insight into how the mind works. However, these insights often seem incompatible, as the debates between symbolic, dynamical, emergentist, sub-symbolic, and grounded approaches to cognition attest. Mental representations—whatever they are—must share many features with each of our theories of representation, and yet there are few hypotheses about how a synthesis could be possible. Here, I develop a theory of the underpinnings of symbolic cognition that shows how sub-symbolic dynamics may give rise (...)
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  11.  9
    Learning Abstract Visual Concepts Via Probabilistic Program Induction in a Language of Thought.Matthew C. Overlan, Robert A. Jacobs & Steven T. Piantadosi - 2017 - Cognition 168:320-334.
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  12.  11
    Post Hoc Analysis Decisions Drive the Reported Reading Time Effects in Hackl, Koster-Hale & Varvoutis.Edward Gibson, Steven T. Piantadosi & Roger Levy - 2017 - Journal of Semantics 34 (3):539-546.
    Hackl, Koster-Hale & Varvoutis provide data that suggest that in a null context, antecedent-contained deletion relative clause structures modifying a quantified object noun phrase are easier to process than those modifying a definite object NP. HKV argue that this pattern of results supports a quantifier-raising analysis of both ACD structures and quantified NPs in object position: under the account they advocate, both ACD resolution and quantified NPs in object position require movement of the object NP to a higher syntactic position. (...)
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  13. Beyond Boolean Logic: Exploring Representation Languages for Learning Complex Concepts.Steven T. Piantadosi, Joshua B. Tenenbaum & Noah D. Goodman - 2010 - In S. Ohlsson & R. Catrambone (eds.), Proceedings of the 32nd Annual Conference of the Cognitive Science Society. Cognitive Science Society. pp. 859--864.
  14.  50
    Quantitative Standards for Absolute Linguistic Universals.Steven T. Piantadosi & Edward Gibson - 2014 - Cognitive Science 38 (4):736-756.
    Absolute linguistic universals are often justified by cross-linguistic analysis: If all observed languages exhibit a property, the property is taken to be a likely universal, perhaps specified in the cognitive or linguistic systems of language learners and users. In many cases, these patterns are then taken to motivate linguistic theory. Here, we show that cross-linguistic analysis will very rarely be able to statistically justify absolute, inviolable patterns in language. We formalize two statistical methods—frequentist and Bayesian—and show that in both it (...)
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  15. The Goldilocks Effect: Infants' Preference for Stimuli That Are Neither Too Predictable nor Too Surprising.Celeste Kidd, Steven T. Piantadosi & Richard N. Aslin - 2010 - In S. Ohlsson & R. Catrambone (eds.), Proceedings of the 32nd Annual Conference of the Cognitive Science Society. Cognitive Science Society. pp. 2476--2481.
     
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