A Case for Deep Learning in Semantics: Response to Pater. Potts, C. Language, 95(1):e115-e124, Linguistic Society of America, 2019. Paper doi abstract bibtex 1 download Pater's (2019) 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.*
@article{pottsCaseDeepLearning2019,
title = {A Case for Deep Learning in Semantics: {{Response}} to {{Pater}}},
shorttitle = {A Case for Deep Learning in Semantics},
author = {Potts, Christopher},
year = {2019},
journal = {Language},
volume = {95},
number = {1},
pages = {e115-e124},
publisher = {Linguistic Society of America},
issn = {1535-0665},
doi = {10.1353/lan.2019.0019},
url = {https://doi.org/10.1353/lan.2019.0019},
urldate = {2024-03-18},
abstract = {Pater's (2019) 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.*},
keywords = {compositionality,connectionism,deep learning,lexical semantics,machine learning,position,semantics,survey},
file = {/Users/shanest/sync/library/Potts/2019/Potts - 2019 - A case for deep learning in semantics Response to2.pdf}
}
Downloads: 1
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