A case for deep learning in semantics

Christopher Potts

arXiv: Computation and Language(2018)

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摘要
Pater's target article builds a persuasive case for establishing stronger ties between theoretical linguistics and connectionism (deep learning). This commentary extends his arguments to semantics, focusing in particular on issues of learning, compositionality, and lexical meaning.
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