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Hits 1 – 13 of 13

1
Rule-based Morphological Inflection Improves Neural Terminology Translation ...
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2
Rule-based Morphological Inflection Improves Neural Terminology Translation ...
Xu, Weijia; Carpuat, Marine. - : arXiv, 2021
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3
Soft Layer Selection with Meta-Learning for Zero-Shot Cross-Lingual Transfer ...
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4
Soft Layer Selection with Meta-Learning for Zero-Shot Cross-Lingual Transfer ...
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5
Improving Multilingual Neural Machine Translation with Auxiliary Source Languages ...
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6
How Does Distilled Data Complexity Impact the Quality and Confidence of Non-Autoregressive Machine Translation? ...
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7
How Does Distilled Data Complexity Impact the Quality and Confidence of Non-Autoregressive Machine Translation? ...
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8
EDITOR: an Edit-Based Transformer with Repositioning for Neural Machine Translation with Soft Lexical Constraints ...
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9
A Non-Autoregressive Edit-Based Approach to Controllable Text Simplification ...
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10
End-to-End Slot Alignment and Recognition for Cross-Lingual NLU ...
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11
EDITOR: an Edit-Based Transformer with Repositioning for Neural Machine Translation with Soft Lexical Constraints ...
Xu, Weijia; Carpuat, Marine. - : arXiv, 2020
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12
Finding stories in the archive through paragraph alignment
In: LLC. - Oxford : Oxford Univ. Press 26 (2011) 3, 359-363
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OLC Linguistik
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13
Finding stories in the archive through paragraph alignment
Xu, Weijia; Esteva, Maria. - : Oxford University Press, 2011
Abstract: Referring to the concept of archival bond, we define stories as formed by documents that relate to a target activity and developed a method called paragraph alignment to find these documents. The method computes archival bond by measuring the cosine similarity between document paragraphs. We tested the method in a chaotic case study collection created in a shared server by different authors. Results demonstrate that this method is more efficient to find stories than calculating the cosine similarity between entire documents. This research helps archivists make sense of collections that are considered inaccessible and whose stories may otherwise be lost.
Keyword: Original Articles
URL: http://llc.oxfordjournals.org/cgi/content/short/26/3/359
https://doi.org/10.1093/llc/fqr017
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