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  1.  63
    A Probabilistic Computational Model of Cross-Situational Word Learning.Afsaneh Fazly, Afra Alishahi & Suzanne Stevenson - 2010 - Cognitive Science 34 (6):1017-1063.
    Words are the essence of communication: They are the building blocks of any language. Learning the meaning of words is thus one of the most important aspects of language acquisition: Children must first learn words before they can combine them into complex utterances. Many theories have been developed to explain the impressive efficiency of young children in acquiring the vocabulary of their language, as well as the developmental patterns observed in the course of lexical acquisition. A major source of disagreement (...)
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  2.  20
    Perspective-taking behavior as the probabilistic weighing of multiple domains.Daphna Heller, Christopher Parisien & Suzanne Stevenson - 2016 - Cognition 149 (C):104-120.
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  3.  22
    A Computational Model of Early Argument Structure Acquisition.Afra Alishahi & Suzanne Stevenson - 2008 - Cognitive Science 32 (5):789-834.
    How children go about learning the general regularities that govern language, as well as keeping track of the exceptions to them, remains one of the challenging open questions in the cognitive science of language. Computational modeling is an important methodology in research aimed at addressing this issue. We must determine appropriate learning mechanisms that can grasp generalizations from examples of specific usages, and that exhibit patterns of behavior over the course of learning similar to those in children. Early learning of (...)
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  4.  16
    Probing Lexical Ambiguity: Word Vectors Encode Number and Relatedness of Senses.Barend Beekhuizen, Blair C. Armstrong & Suzanne Stevenson - 2021 - Cognitive Science 45 (5):e12943.
    Lexical ambiguity—the phenomenon of a single word having multiple, distinguishable senses—is pervasive in language. Both the degree of ambiguity of a word (roughly, its number of senses) and the relatedness of those senses have been found to have widespread effects on language acquisition and processing. Recently, distributional approaches to semantics, in which a word's meaning is determined by its contexts, have led to successful research quantifying the degree of ambiguity, but these measures have not distinguished between the ambiguity of words (...)
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  5.  26
    Modeling Reference Production as the Probabilistic Combination of Multiple Perspectives.Mindaugas Mozuraitis, Suzanne Stevenson & Daphna Heller - 2018 - Cognitive Science 42 (S4):974-1008.
    While speakers have been shown to adapt to the knowledge state of their addressee in choosing referring expressions, they often also show some egocentric tendencies. The current paper aims to provide an explanation for this “mixed” behavior by presenting a model that derives such patterns from the probabilistic combination of both the speaker's and the addressee's perspectives. To test our model, we conducted a language production experiment, in which participants had to refer to objects in a context that also included (...)
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  6. A probabilistic incremental model of word learning in the presence of referential uncertainty.Afsaneh Fazly, Afra Alishahi & Suzanne Stevenson - 2008 - In B. C. Love, K. McRae & V. M. Sloutsky (eds.), Proceedings of the 30th Annual Conference of the Cognitive Science Society. Cognitive Science Society.
  7.  29
    More Than the Eye Can See: A Computational Model of Color Term Acquisition and Color Discrimination.Barend Beekhuizen & Suzanne Stevenson - 2018 - Cognitive Science 42 (8):2699-2734.
    We explore the following two cognitive questions regarding crosslinguistic variation in lexical semantic systems: Why are some linguistic categories—that is, the associations between a term and a portion of the semantic space—harder to learn than others? How does learning a language‐specific set of lexical categories affect processing in that semantic domain? Using a computational word‐learner, and the domain of color as a testbed, we investigate these questions by modeling both child acquisition of color terms and adult behavior on a non‐verbal (...)
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  8.  19
    The Emergence of Gender Associations in Child Language Development.Ben Prystawski, Erin Grant, Aida Nematzadeh, Spike W. S. Lee, Suzanne Stevenson & Yang Xu - 2022 - Cognitive Science 46 (6):e13146.
    Cognitive Science, Volume 46, Issue 6, June 2022.
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