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Published on: June 3, 2013
Is human compositionality meta-learned?
Jacob Russin1,2, Sam Whitman McGrath3, Ellie Pavlick1
1Department of Computer Science, Brown University, Providence, RI, USA jake_russin@brown.edu ellie_pavlick@brown.edu https://jlrussin.github.io/ https://cs.brown.edu/people/epavlick/.
Abstract:
Recent studies suggest that meta-learning may provide an original solution to an enduring puzzle about whether neural networks can explain compositionality - in particular, by raising the prospect that compositionality can be understood as an emergent property of an inner-loop learning algorithm. We elaborate on this hypothesis and consider its empirical predictions regarding the neural mechanisms and development of human compositionality.
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