13 found
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  1.  44
    Word learning emerges from the interaction of online referent selection and slow associative learning.Bob McMurray, Jessica S. Horst & Larissa K. Samuelson - 2012 - Psychological Review 119 (4):831-877.
  2.  43
    Early noun vocabularies: do ontology, category structure and syntax correspond?Larissa K. Samuelson & Linda B. Smith - 1999 - Cognition 73 (1):1-33.
  3.  27
    Word-Object Learning via Visual Exploration in Space (WOLVES): A neural process model of cross-situational word learning.Ajaz A. Bhat, John P. Spencer & Larissa K. Samuelson - 2022 - Psychological Review 129 (4):640-695.
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  4.  42
    What’s new? Children prefer novelty in referent selection.Jessica S. Horst, Larissa K. Samuelson, Sarah C. Kucker & Bob McMurray - 2011 - Cognition 118 (2):234-244.
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  5.  47
    Too Much of a Good Thing: How Novelty Biases and Vocabulary Influence Known and Novel Referent Selection in 18‐Month‐Old Children and Associative Learning Models.Sarah C. Kucker, Bob McMurray & Larissa K. Samuelson - 2018 - Cognitive Science 42 (S2):463-493.
    Identifying the referent of novel words is a complex process that young children do with relative ease. When given multiple objects along with a novel word, children select the most novel item, sometimes retaining the word‐referent link. Prior work is inconsistent, however, on the role of object novelty. Two experiments examine 18‐month‐old children's performance on referent selection and retention with novel and known words. The results reveal a pervasive novelty bias on referent selection with both known and novel names and, (...)
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  6.  37
    The dynamic nature of knowledge: Insights from a dynamic field model of children’s novel noun generalization.Larissa K. Samuelson, Anne R. Schutte & Jessica S. Horst - 2009 - Cognition 110 (3):322-345.
  7.  83
    Grounding Cognitive‐Level Processes in Behavior: The View From Dynamic Systems Theory.Larissa K. Samuelson, Gavin W. Jenkins & John P. Spencer - 2015 - Topics in Cognitive Science 7 (2):191-205.
    Marr's seminal work laid out a program of research by specifying key questions for cognitive science at different levels of analysis. Because dynamic systems theory focuses on time and interdependence of components, DST research programs come to very different conclusions regarding the nature of cognitive change. We review a specific DST approach to cognitive-level processes: dynamic field theory. We review research applying DFT to several cognitive-level processes: object permanence, naming hierarchical categories, and inferring intent, that demonstrate the difference in understanding (...)
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  8.  45
    Come down from the clouds: Grounding Bayesian insights in developmental and behavioral processes.Gavin W. Jenkins, Larissa K. Samuelson & John P. Spencer - 2011 - Behavioral and Brain Sciences 34 (4):204-206.
    According to Jones & Love (J&L), Bayesian theories are too often isolated from other theories and behavioral processes. Here, we highlight examples of two types of isolation from the field of word learning. Specifically, Bayesian theories ignore emergence, critical to development theory, and have not probed the behavioral details of several key phenomena, such as the effect.
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  9.  17
    Learning words in space and time: Contrasting models of the suspicious coincidence effect.Gavin W. Jenkins, Larissa K. Samuelson, Will Penny & John P. Spencer - 2021 - Cognition 210 (C):104576.
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  10.  26
    Object and word familiarization differentially boost retention in fast-mapping.Sarah C. Kucker & Larissa K. Samuelson - 2010 - In S. Ohlsson & R. Catrambone (eds.), Proceedings of the 32nd Annual Conference of the Cognitive Science Society. Cognitive Science Society.
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  11.  26
    Introduction to the Special Issue Honoring the 2013 David E. Rumelhart Prize Recipient Linda B. Smith.Larissa K. Samuelson - 2017 - Cognitive Science 41 (S1):4-4.
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  12.  83
    Language as shaped by the brain; the brain as shaped by development.Joseph C. Toscano, Lynn K. Perry, Kathryn L. Mueller, Allison F. Bean, Marcus E. Galle & Larissa K. Samuelson - 2008 - Behavioral and Brain Sciences 31 (5):535-536.
    Though we agree with their argument that language is shaped by domain-general learning processes, Christiansen & Chater (C&C) neglect to detail how the development of these processes shapes language change. We discuss a number of examples that show how developmental processes at multiple levels and timescales are critical to understanding the origin of domain-general mechanisms that shape language evolution.
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  13.  54
    Non‐Bayesian Noun Generalization in 3‐ to 5‐Year‐Old Children: Probing the Role of Prior Knowledge in the Suspicious Coincidence Effect. [REVIEW]Gavin W. Jenkins, Larissa K. Samuelson, Jodi R. Smith & John P. Spencer - 2015 - Cognitive Science 39 (2):268-306.
    It is unclear how children learn labels for multiple overlapping categories such as “Labrador,” “dog,” and “animal.” Xu and Tenenbaum suggested that learners infer correct meanings with the help of Bayesian inference. They instantiated these claims in a Bayesian model, which they tested with preschoolers and adults. Here, we report data testing a developmental prediction of the Bayesian model—that more knowledge should lead to narrower category inferences when presented with multiple subordinate exemplars. Two experiments did not support this prediction. Children (...)
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