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Hits 1 – 2 of 2
1
From Masked Language Modeling to Translation: Non-English Auxiliary Tasks Improve Zero-shot Spoken Language Understanding ...
van der Goot, Rob
;
Sharaf, Ibrahim
;
Imankulova, Aizhan
. - : arXiv, 2021
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Neural Combinatory Constituency Parsing ...
The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021
;
Chen, Zhousi
;
Imankulova, Aizhan
;
Komachi, Mamoru
;
Zhang, Longtu
. - : Underline Science Inc., 2021
Abstract:
Read paper: https://www.aclanthology.org/2021.findings-acl.194 Abstract: We propose two fast neural combinatory models for constituency parsing: binary and multi-branching. Our models decompose the bottom-up parsing process into 1) classification of tags, labels, and binary orientations or chunks and 2) vector composition based on the computed orientations or chunks. These models have theoretical sub-quadratic complexity and empirical linear complexity. The binary model achieves an F1 score of 92.54 on Penn Treebank, speeding at 1327.2 sents/sec. Both the models with XLNet provide near state-of-the-art accuracies for English. Syntactic branching tendency and headedness of a language are observed during the training and inference processes for Penn Treebank, Chinese Treebank, and Keyaki Treebank (Japanese). ...
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Computational Linguistics
;
Condensed Matter Physics
;
Deep Learning
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Electromagnetism
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FOS Physical sciences
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Information and Knowledge Engineering
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Neural Network
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Semantics
URL:
https://underline.io/lecture/26285-neural-combinatory-constituency-parsing
https://dx.doi.org/10.48448/r4zf-ny24
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