[PDF] Top 20 Neural Machine Translation with Source Side Latent Graph Parsing
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Neural Machine Translation with Source Side Latent Graph Parsing
... novel neural ma- chine translation model which jointly learns translation and source-side latent graph representations of ...a latent graph parser as part of ... See full document
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Incorporating Source Syntax into Transformer Based Neural Machine Translation
... corporating source-side syntactic annotations into a Transformer-based neural machine translation ...the source sentences as well as unparsed source sentences directly ... See full document
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Unsupervised Source Hierarchies for Low Resource Neural Machine Translation
... Incorporating source syntactic infor- mation into neural machine translation (NMT) has recently proven success- ful (Eriguchi et ...for neural machine translation; this ... See full document
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Multi Source Neural Machine Translation with Missing Data
... Multi-source translation is an approach to exploit multiple inputs ...multi-source neural machine translation (NMT) using an incomplete multilingual corpus in which some transla- ... See full document
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Ensemble Learning for Multi Source Neural Machine Translation
... in neural machine translation ...different source languages into the same target language, i.e., multi-source ensembles, a method recently introduced by Firat et ...English ... See full document
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Exploiting Source side Monolingual Data in Neural Machine Translation
... Neural Machine Translation (NMT) based on the encoder-decoder architecture has recently become a new ...the source-side monolingual data is not fully explored although it should be ... See full document
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Neural Machine Translation with Source Dependency Representation
... for Neural Machine Translation (NMT), such as concatenating representations of source word and its dependency label ...with source dependency represen- tation to improve ... See full document
7
OpenNMT: Open Source Toolkit for Neural Machine Translation
... C/Mobile/GPU Translation Training NMT systems requires some code complexity to fa- cilitate fast ...different translation deployments specialized for different run-time environments: a batched CPU/GPU ... See full document
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Modeling Source Syntax for Neural Machine Translation
... Due to the capability of carrying syntactic infor- mation in source annotation vectors, we conjec- ture that our model with source syntax is also beneficial for alignment. To test this hypothe- sis, we ... See full document
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Exploiting Semantics in Neural Machine Translation with Graph Convolutional Networks
... In the first sentence, the only difference is in the choice of the preposition for the argument Mark . Note that the argument is correctly assigned to role A2 (‘Buyer’) by the semantic role labeler. The BiRNN model ... See full document
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Graph Convolutional Encoders for Syntax aware Neural Machine Translation
... into neural attention-based encoder- decoder models for machine ...on graph-convolutional networks (GCNs), a recent class of neural networks developed for modeling graph-structured ... See full document
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Controlling Politeness in Neural Machine Translation via Side Constraints
... a neural machine translation (NMT) system, which allows us to control the level of politeness at test time through what we call side ...for translation between languages where the T-V ... See full document
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Graph Based Translation Memory for Neural Machine Translation
... involving graph structures to improve ...a translation graph ...best translation from this con- strained ...discrete graph into the continu- ous vectors from the point view of ... See full document
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Latent Part of Speech Sequences for Neural Machine Translation
... get side syntax model that allows exhaustive ex- ploration of the latent states to ensure a better translation ...the source text and the partial translation ...of latent state ... See full document
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Target side Word Segmentation Strategies for Neural Machine Translation
... statistical machine translation systems, mostly on the source language side, but sometimes also on the target side (Sennrich et ... See full document
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OpenNMT: Neural Machine Translation Toolkit
... Neural machine translation (NMT) is a new methodology for machine translation that has led to remarkable improvements, particularly in terms of human evaluation, compared to rule-based ... See full document
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Towards Neural Machine Translation with Latent Tree Attention
... of machine translation, pairing a recurrent neural net- work grammar encoder with a novel atten- tional RNNG decoder and applying pol- icy gradient reinforcement learning to in- duce unsupervised ... See full document
5
Modeling Target Side Inflection in Neural Machine Translation
... Another successful attempt to learn novel in- flections in SMT is back-translation (Bojar and Tamchyna, 2011). By using an MT system trained to translate lemmas in the opposite direction, it is possible to create ... See full document
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AMR Parsing as Graph Prediction with Latent Alignment
... statistical machine transla- tion (Brown et al., 1993). Such translation mod- els have also been successfully applied to semantic parsing tasks ...AMR parsing, another way to avoid us- ing ... See full document
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Statistical Machine Translation by Parsing
... Figure 1 shows some of the ways in which ordi- nary parsing can be generalized. A synchronous parser is an algorithm that can infer the syntactic structure of each component text in a multitext and simultaneously ... See full document
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