[PDF] Top 20 Competence based Curriculum Learning for Neural Machine Translation
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Competence based Curriculum Learning for Neural Machine Translation
... riculum learning for NMT, although other related works have met with mixed ...several curriculum heuristics on training a translation system for a sin- gle epoch, presenting the training examples in ... See full document
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Multi agent Learning for Neural Machine Translation
... There have been many alternatives to improve the diversity of models even based on the Trans- former model (Vaswani et al., 2017). For exam- ple, decoding in the opposite direction usually re- sults in different ... See full document
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Neural Machine Translation with Adequacy-Oriented Learning
... Although Neural Machine Translation (NMT) models have advanced state-of-the-art performance in machine translation, they face problems like the inadequate ...real translation ... See full document
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A Study of Reinforcement Learning for Neural Machine Translation
... A natural extension of previous discussions is to combine both the source-side and target-side mono- lingual data for RL training. We consider two com- binations, the sequential method and the unified method. The former ... See full document
10
Learning to Actively Learn Neural Machine Translation
... active learning (AL) methods for machine translation (MT) rely on ...language-pair based on AL simulations, and then transfer it to the low- resource language-pair of ... See full document
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NICT’s participation to WAT 2019: Multilingualism and Multi step Fine Tuning for Low Resource NMT
... Neural machine translation (NMT) (Cho et ...alignments, translation rules, and complicated decoding algorithms, which are the characteris- tics of phrase-based statistical ... See full document
5
A Model of Competence for Corpus Based Machine Translation
... A translation can only be generated if an appropriate example translation is available in the reference ...the learning pro- cess implement in order to generate an appropriate understanding of the ... See full document
5
Character based Neural Machine Translation
... Character-based Machine Translation Word embeddings have been shown to boost the performance in many NLP tasks, including ma- chine ...lookup- based embeddings are limited to a finite-size vo- ... See full document
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Learning from Chunk based Feedback in Neural Machine Translation
... An example where the NMT system with chunk- based feedback yields a better translation in com- parison to other systems is the German sentence “Die Krise ist vor¨uber.” (“The crisis is over.“). The German ... See full document
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Active Learning for Interactive Neural Machine Translation of Data Streams
... All these works were based on SMT systems. However, the recently introduced NMT paradigm (Sutskever et al., 2014; Bahdanau et al., 2015) has irrupted as the current state-of-the-art for MT (Bo- jar et al., 2017). ... See full document
10
Imitation Learning for Non Autoregressive Neural Machine Translation
... the translation quality is largely sacrificed since the intrinsic dependency within the natural language sentence is ...refinement based on latent variable model and denoising ...of translation tasks ... See full document
9
Learning to Parse and Translate Improves Neural Machine Translation
... of neural machine translation, which results in two separate models rather than a single end-to-end ...trained translation model strictly requires the availability of external tools during ... See full document
7
Ensemble Learning for Multi Source Neural Machine Translation
... that translation systems from different source language into the same target language have complementary strengths and weak- nesses in terms of translation performance and introduce an approach that can ... See full document
10
Learning to Translate in Real time with Neural Machine Translation
... sized segments of the input sequence and outputs tokens based on each segment in real-time. It is trained with alignment information using super- vised learning. A similar idea for online ASR is proposed by ... See full document
10
A Multi Task Architecture on Relevance based Neural Query Translation
... multi-task learning approach to train a Neural Machine Translation (NMT) model with a Relevance-based Auxiliary Task (RAT) for search query ...task learning architecture that ... See full document
6
Reinforcement Learning based Curriculum Optimization for Neural Machine Translation
... Figure 3 shows a coarse visualization of the hand- optimized policy of Wang et al. (2018), adapted to our 6-bin scenario, compared to the Q-learning policy on the same scenario. The former, by de- sign, telescopes ... See full document
8
Improving Anaphora Resolution in Neural Machine Translation Using Curriculum Learning
... our curriculum learning approach does not affect performance in this ...the curriculum learning approach only manages to match the ...training curriculum from 100% grad- ually to 0% ... See full document
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Curriculum Learning and Minibatch Bucketing in Neural Machine Translation
... Machine translation (MT) has recently seen an- other major change of ...rule based approaches which worked suc- cessfully for small ...to neural MT (NMT; Collobert et ... See full document
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Curriculum Learning for Domain Adaptation in Neural Machine Translation
... for curriculum learning ...when curriculum learning is ap- ...with curriculum learning on new tasks; a potential direction for fu- ture work may be a curriculum that ... See full document
13
Graph Based Translation Memory for Neural Machine Translation
... subsets based on the averaged similarity of each sentence in the retrieved trans- lation ...the translation memory indeed brings improvements of translation quality over all similarity ... See full document
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