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Integrating Weakly Supervised Word Sense Disambiguation into Neural Machine Translation ...
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Integrating Weakly Supervised Word Sense Disambiguation into Neural Machine Translation ...
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Integrating Weakly Supervised Word Sense Disambiguation into Neural Machine Translation ...
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Machine Translation of Low-Resource Spoken Dialects: Strategies for Normalizing Swiss German ...
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DiscoMT 2016 Shared Task on Cross-lingual Pronoun Prediction
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Consistent Translation of Repeated Nouns using Syntactic and Semantic Cues ...
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Multilingual Hierarchical Attention Networks for Document Classification ...
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Multilingual Hierarchical Attention Networks for Document Classification ...
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Multilingual Hierarchical Attention Networks for Document Classification ...
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Machine Translation of Spanish Personal and Possessive Pronouns Using Anaphora Probabilities ...
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Self-Attentive Residual Decoder for Neural Machine Translation ...
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Abstract:
Neural sequence-to-sequence networks with attention have achieved remarkable performance for machine translation. One of the reasons for their effectiveness is their ability to capture relevant source-side contextual information at each time-step prediction through an attention mechanism. However, the target-side context is solely based on the sequence model which, in practice, is prone to a recency bias and lacks the ability to capture effectively non-sequential dependencies among words. To address this limitation, we propose a target-side-attentive residual recurrent network for decoding, where attention over previous words contributes directly to the prediction of the next word. The residual learning facilitates the flow of information from the distant past and is able to emphasize any of the previously translated words, hence it gains access to a wider context. The proposed model outperforms a neural MT baseline as well as a memory and self-attention network on three language pairs. The analysis of the ... : Accepted on NAACL-HLT 2018, Volume: Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers) ...
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Keyword:
Computation and Language cs.CL; FOS Computer and information sciences
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URL: https://dx.doi.org/10.48550/arxiv.1709.04849 https://arxiv.org/abs/1709.04849
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Sense-Aware Statistical Machine Translation using Adaptive Context-Dependent Clustering ...
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Sense-Aware Statistical Machine Translation using Adaptive Context-Dependent Clustering ...
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Multilingual Hierarchical Attention Networks for Document Classification
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In: http://infoscience.epfl.ch/record/231134 (2017)
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Cross-lingual Transfer for News Article Labeling: Benchmarking Statistical and Neural Models
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In: http://infoscience.epfl.ch/record/231130 (2017)
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