[PDF] Top 20 Memory Augmented Neural Networks for Machine Translation
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Memory Augmented Neural Networks for Machine Translation
... by the encoder and read from by the decoder. But attentional encoder-decoders do not have the same range of capabilities as MANNs such as the Neural Turing Machine (NTM) (Graves et al., 2014) or ... See full document
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Sentence Simplification with Memory Augmented Neural Networks
... in neural machine translation have paved the way for novel approaches to the ...mented memory capacities called Neural Se- mantic Encoders (Munkhdalai and Yu, 2017) for sentence ... See full document
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Machine Translation Evaluation using Recurrent Neural Networks
... Recent best performing metrics in the WMT- 14 metric shared task (Mach´acek and Bojar, 2014) used a combination of different metrics. The top performing system DiskoTK-Party-Tuned (Joty et al., 2014) in the WMT-14 task ... See full document
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Holographic Generative Memory: Neurally Inspired One-Shot Learning with Memory Augmented Neural Networks
... many neural network applications like computer ...single-task neural networks since it measures uncertainty we typically cannot reduce in that ... See full document
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Bidirectional Generative Adversarial Networks for Neural Machine Translation
... However, in this training process, the discrim- inator typically suffers from inadequate training problem, leading to the instability of GAN train- ing. In practice, sampling large translation candi- dates is ... See full document
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A Multi Stage Memory Augmented Neural Network for Machine Reading Comprehension
... To show the effectiveness of our method in addressing long-term dependencies, we collected two examples from the devset of TriviaQA, shown in Table 6. Finding an answer in these examples require resolving long-term ... See full document
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Additive Neural Networks for Statistical Machine Translation
... the translation model (Nguyen et ...the translation per- formance may not improve, or may even decrease, after one integrates additional features into the ...the translation performance, but after a ... See full document
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Towards Linear Time Neural Machine Translation with Capsule Networks
... capsule networks is to measure the input and output ...capsule networks often resort to a straightforward strategy in which the “fusion” decisions ...functional networks to release the scoring duty, ... See full document
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A Recurrent Neural Networks Approach for Estimating the Quality of Machine Translation Output
... recurrent neural networks for estimating the quality of machine translation ...recurrent neural network architecture both on source and target sen- tence to fully utilize the ... See full document
5
Scaling Neural Machine Translation
... + overlap comm+bwd 128 402k 1 26.5 9.7k 1.82M 32 44.7x Table 1 : Training time (min) for reduced precision ( 16-bit ), cumulating gradients over multiple back- wards (cumul), increasing learning rate (2x lr) and ... See full document
9
Boosting Neural Machine Translation
... two networks to encode the source and decode the target at the same ...convolutional neural networks to build the sys- tem with a nature of ... See full document
6
Hungarian translators’ perceptions of Neural Machine Translation in the European Commission
... offers translation services to other Commission Directorates-General, who send translation requests to a central DGT service that pre-processes texts automatically using various ...normative memory, ... See full document
7
Exploiting Semantics in Neural Machine Translation with Graph Convolutional Networks
... of machine translation ...into neural machine transla- tion. We use Graph Convolutional Networks (GCNs) to inject a semantic bias into sentence encoders and achieve improvements in BLEU ... See full document
7
Combining Translation Memory with Neural Machine Translation
... plicated translation pairs between ...all translation pairs, which guarantees that these sentence-level translation pairs are inde- pendently sampled from the original ...lation memory ... See full document
8
Document Context Neural Machine Translation with Memory Networks
... dual memory model, we look at the first sentence exam- ple in Table ...the translation. On the other hand, the single memory models are better in delivering some, if not all, of the underlying ... See full document
10
Graph Based Translation Memory for Neural Machine Translation
... posed model, G-TFM. There’s no wonder that TFM takes the fewest words to encode because no extra TM is included. These statistics indicate that under the scenario of incorpo- rating TM in NMT, our model requires the ... See full document
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Memory augmented Neural Machine Translation
... of neural models: the trans- lation function, represented by various neural net- works, is shared amongst all of the translation pairs, so high-frequency and low-frequency pairs impact each other by ... See full document
10
Paraphrasing Revisited with Neural Machine Translation
... of neural machine translation, a new approach to machine transla- tion based purely on neural networks (Kalchbren- ner and Blunsom, 2013; Bahdanau et ...deep neural ... See full document
13
Residual Stacking of RNNs for Neural Machine Translation
... of machine translation is greatly improved by applying neural networks par- tially in a Statistical Machine Translation (SMT) pipeline (Zou et ...end-to-end neural network ... See full document
7
Memory enhanced Decoder for Neural Machine Translation
... There is a long thread of work aiming to im- prove the ability of RNN in remembering long se- quences, with the long short-term memory RNN (LSTM) (Hochreiter and Schmidhuber, 1997) be- ing the most salient ... See full document
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