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Few-shot learning through contextual data augmentation
In: EACL 2021 - 16th Conference of the European Chapter of the Association for Computational Linguistics ; https://hal.inria.fr/hal-03121971 ; EACL 2021 - 16th Conference of the European Chapter of the Association for Computational Linguistics, Apr 2021, Kiev / Virtual, Ukraine (2021)
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2
Cross-lingual Intermediate Fine-tuning improves Dialogue State Tracking ...
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3
CoPHE: A Count-Preserving Hierarchical Evaluation Metric in Large-Scale Multi-Label Text Classification ...
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4
Exploring Unsupervised Pretraining Objectives for Machine Translation ...
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Cross-lingual Intermediate Fine-tuning improves Dialogue State Tracking ...
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6
Architecture of a Scalable, Secure and Resilient Translation Platform for Multilingual News Media
In: Proceedings of the 1st International Workshop on Language Technology Platforms ; 1st International Workshop on Language Technology Platforms ; https://hal.archives-ouvertes.fr/hal-02900633 ; 1st International Workshop on Language Technology Platforms, 2020, Marseille, France. pp.16-21 (2020)
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The University of Edinburgh’s English-Tamil and English-Inuktitut Submissions to the WMT20 News Translation Task
In: Proceedings of the 5th Conference on Machine Translation ; 5th Conference on Machine Translation ; https://hal.archives-ouvertes.fr/hal-02981153 ; 5th Conference on Machine Translation, Nov 2020, Online, Unknown Region (2020)
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Bridging Linguistic Typology and Multilingual Machine Translation with Multi-View Language Representations ...
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9
Architecture of a Scalable, Secure and Resilient Translation Platform for Multilingual News Media ...
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10
Architecture of a Scalable, Secure and Resilient Translation Platform for Multilingual News Media ...
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11
MultiWord Expression Aware Neural Machine Translation ...
Zaninello, Andrea; Birch, Alexandra. - : Zenodo, 2020
Abstract: Multiword Expressions (MWEs) are a frequently occurring phenomenon found in all natural languages that is of great importance to linguistic theory, natural language processing applications, and machine translation systems. Neural Machine Translation (NMT) architectures do not handle these expression well and previous studies have not explicitly addressed MWEs in this framework. In this work, we show that using external linguistic resources and data augmentation we can improve both translations of MWEs that occur in the source, and the generation of MWEs on the target, and improve performance by up to 5.09 BLEU points on MWE test sets. We also devise a MWE score to specifically assess the quality of MWE translation which agrees with human evaluation. We make available the MWEscore implementation – along with MWE-annotated training sets and corpus-based lists of MWEs – for reproduction and extension. ...
Keyword: multiword expressions, neural machine translation, evaluation
URL: https://dx.doi.org/10.5281/zenodo.3923508
https://zenodo.org/record/3923508
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12
MultiWord Expression Aware Neural Machine Translation ...
Zaninello, Andrea; Birch, Alexandra. - : Zenodo, 2020
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13
A Latent Morphology Model for Open-Vocabulary Neural Machine Translation ...
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14
A Latent Morphology Model for Open-Vocabulary Neural Machine Translation ...
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15
The University of Edinburgh’s Submissions to the WMT19 News Translation Task
In: 4th Conference on Machine Translation ; https://hal.inria.fr/hal-02986330 ; 4th Conference on Machine Translation, 2019, Florence, Italy (2019)
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16
Towards a Multi-view Language Representation: A Shared Space of Discrete and Continuous Language Features ...
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17
Towards a Multi-view Language Representation: A Shared Space of Discrete and Continuous Language Features ...
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18
On the Importance of Word Boundaries in Character-level Neural Machine Translation ...
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19
A Latent Morphology Model for Open-Vocabulary Neural Machine Translation ...
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20
Generalization in Generation: A closer look at Exposure Bias
In: Proceedings of the 3rd Workshop on Neural Generation and Translation (2019)
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