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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 (3)
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Simple Search
Hits 1 – 11 of 11
1
Signed Coreference Resolution ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Yin, Kayo
. - : Underline Science Inc., 2021
BASE
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2
Including Signed Languages in Natural Language Processing ...
Yin, Kayo
;
Moryossef, Amit
;
Hochgesang, Julie
. - : arXiv, 2021
BASE
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3
Including Signed Languages in Natural Language Processing ...
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
;
Alikhani, Malihe
;
Goldberg, Yoav
. - : Underline Science Inc., 2021
BASE
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4
When Does Translation Require Context? A Data-driven, Multilingual Exploration ...
Yin, Kayo
;
Fernandes, Patrick
;
Martins, André F. T.
. - : arXiv, 2021
BASE
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5
Measuring and Increasing Context Usage in Context-Aware Machine Translation ...
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
;
Fernandes, Patrick
;
Martins, Andre
;
Neubig, Graham
;
Yin, Kayo
. - : Underline Science Inc., 2021
Abstract:
Read paper: https://www.aclanthology.org/2021.acl-long.505 Abstract: Recent work in neural machine translation has demonstrated both the necessity and feasibility of using inter-sentential context, context from sentences other than those currently being translated. However, while many current methods present model architectures that theoretically can use this extra context, it is often not clear how much they do actually utilize it at translation time. In this paper, we introduce a new metric, conditional cross-mutual information, to quantify usage of context by these models. Using this metric, we measure how much document-level machine translation systems use particular varieties of context. We find that target context is referenced more than source context, and that including more context has a diminishing affect on results. We then introduce a new, simple training method, context-aware word dropout, to increase the usage of context by context-aware models. Experiments show that our method not only ...
Keyword:
Computational Linguistics
;
Condensed Matter Physics
;
Deep Learning
;
Electromagnetism
;
FOS Physical sciences
;
Information and Knowledge Engineering
;
Neural Network
;
Semantics
URL:
https://underline.io/lecture/25724-measuring-and-increasing-context-usage-in-context-aware-machine-translation
https://dx.doi.org/10.48448/x7mr-nt94
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6
Data Augmentation for Sign Language Gloss Translation ...
Moryossef, Amit
;
Yin, Kayo
;
Neubig, Graham
. - : arXiv, 2021
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7
Do Context-Aware Translation Models Pay the Right Attention? ...
Yin, Kayo
;
Fernandes, Patrick
;
Pruthi, Danish
. - : arXiv, 2021
BASE
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8
When is Wall a Pared and when a Muro? -- Extracting Rules Governing Lexical Selection ...
Chaudhary, Aditi
;
Yin, Kayo
;
Anastasopoulos, Antonios
. - : arXiv, 2021
BASE
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9
When is Wall a Pared and when a Muro?: Extracting Rules Governing Lexical Selection ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Anastasopoulos, Antonios
;
Chaudhary, Aditi
. - : Underline Science Inc., 2021
BASE
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10
Do Context-Aware Translation Models Pay the Right Attention? ...
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
;
Chaudhary, Aditi
;
Fernandes, Patrick
. - : Underline Science Inc., 2021
BASE
Show details
11
Better Sign Language Translation with STMC-Transformer ...
Yin, Kayo
;
Read, Jesse
. - : arXiv, 2020
BASE
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