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  1. Seeing and speaking: How verbal 'description length' encodes visual complexity.Zekun Sun & Chaz Firestone - 2021 - Journal of Experimental Psychology: General (1):82-96.
    What is the relationship between complexity in the world and complexity in the mind? Intuitively, increasingly complex objects and events should give rise to increasingly complex mental representations (or perhaps a plateau in complexity after a certain point). However, a counterintuitive possibility with roots in information theory is an inverted U-shaped relationship between the “objective” complexity of some stimulus and the complexity of its mental representation, because excessively complex patterns might be characterized by surprisingly short computational descriptions (e.g., if they (...)
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  • Drawing improves memory: The importance of multimodal encoding context.Jeffrey D. Wammes, Tanya R. Jonker & Myra A. Fernandes - 2019 - Cognition 191 (C):103955.
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  • Consistency and Variation in Reasoning About Physical Assembly.William P. McCarthy, David Kirsh & Judith E. Fan - 2023 - Cognitive Science 47 (12):e13397.
    The ability to reason about how things were made is a pervasive aspect of how humans make sense of physical objects. Such reasoning is useful for a range of everyday tasks, from assembling a piece of furniture to making a sandwich and knitting a sweater. What enables people to reason in this way even about novel objects, and how do people draw upon prior experience with an object to continually refine their understanding of how to create it? To explore these (...)
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  • Individual differences in internal models explain idiosyncrasies in scene perception.Gongting Wang, Matthew J. Foxwell, Radoslaw M. Cichy, David Pitcher & Daniel Kaiser - 2024 - Cognition 245 (C):105723.
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  • For deep networks, the whole equals the sum of the parts.Philip J. Kellman, Nicholas Baker, Patrick Garrigan, Austin Phillips & Hongjing Lu - 2023 - Behavioral and Brain Sciences 46:e396.
    Deep convolutional networks exceed humans in sensitivity to local image properties, but unlike biological vision systems, do not discover and encode abstract relations that capture important properties of objects and events in the world. Coupling network architectures with additional machinery for encoding abstract relations will make deep networks better models of human abilities and more versatile and capable artificial devices.
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  • Visual explanations prioritize functional properties at the expense of visual fidelity.Holly Huey, Xuanchen Lu, Caren M. Walker & Judith E. Fan - 2023 - Cognition 236 (C):105414.
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