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 [BibTeX] [Marc21]
The Unstoppable Rise of Computational Linguistics in Deep Learning
Type of publication: Conference paper
Citation: Henderson_ACL2020_2020
Publication status: Published
Booktitle: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
Year: 2020
Month: July
Pages: 6294-6306
Publisher: Association for Computational Linguistics
Location: Online
Organization: Association for Computational Linguistics
URL: https://www.aclweb.org/antholo...
DOI: 10.18653/v1/2020.acl-main.561
Abstract: In this paper, we trace the history of neural networks applied to natural language understanding tasks, and identify key contributions which the nature of language has made to the development of neural network architectures. We focus on the importance of variable binding and its instantiation in attention-based models, and argue that Transformer is not a sequence model but an induced-structure model. This perspective leads to predictions of the challenges facing research in deep learning architectures for natural language understanding.
Projects Idiap
Authors Henderson, James
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