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  1. Testing Global Memory Models Using ROC Curves.Roger Ratcliff, Ching-fan Sheu & Scott D. Gronlund - 1992 - Psychological Review 99 (3):518-535.
  • Toward an Instance Theory of Automatization.Gordon D. Logan - 1988 - Psychological Review 95 (4):492-527.
  • The Item Versus the Object in Memory: On the Implausibility of Overwriting As a Mechanism for Forgetting in Short-Term Memory.C. Philip Beaman & Dylan M. Jones - 2016 - Frontiers in Psychology 7.
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  • Processing Capacity Defined by Relational Complexity: Implications for Comparative, Developmental, and Cognitive Psychology.Graeme S. Halford, William H. Wilson & Steven Phillips - 1998 - Behavioral and Brain Sciences 21 (6):803-831.
    Working memory limits are best defined in terms of the complexity of the relations that can be processed in parallel. Complexity is defined as the number of related dimensions or sources of variation. A unary relation has one argument and one source of variation; its argument can be instantiated in only one way at a time. A binary relation has two arguments, two sources of variation, and two instantiations, and so on. Dimensionality is related to the number of chunks, because (...)
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  • Models of Memory.Jeroen Gw Raaijmakers & Richard M. Shiffrin - 2002 - In J. Wixted & H. Pashler (eds.), Stevens' Handbook of Experimental Psychology. Wiley.
  • Squeezing Through the Now-or-Never Bottleneck: Reconnecting Language Processing, Acquisition, Change, and Structure.Nick Chater & Morten H. Christiansen - 2016 - Behavioral and Brain Sciences 39.
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  • Feature-Sampling and Random-Walk Models of Individual-Stimulus Recognition.Koen Lamberts, Noellie Brockdorff & Evan Heit - 2003 - Journal of Experimental Psychology: General 132 (3):351.
  • A Largeā€Scale Analysis of Variance in Written Language.Brendan T. Johns & Randall K. Jamieson - 2018 - Cognitive Science 42 (4):1360-1374.
    The collection of very large text sources has revolutionized the study of natural language, leading to the development of several models of language learning and distributional semantics that extract sophisticated semantic representations of words based on the statistical redundancies contained within natural language. The models treat knowledge as an interaction of processing mechanisms and the structure of language experience. But language experience is often treated agnostically. We report a distributional semantic analysis that shows written language in fiction books varies appreciably (...)
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