[PDF] Top 20 Instance Weighting for Neural Machine Translation Domain Adaptation
Has 10000 "Instance Weighting for Neural Machine Translation Domain Adaptation" found on our website. Below are the top 20 most common "Instance Weighting for Neural Machine Translation Domain Adaptation".
Instance Weighting for Neural Machine Translation Domain Adaptation
... Philipp Koehn, Hieu Hoang, Alexandra Birch, Chris Callison-Burch, Marcello Federico, Nicola Bertoldi, Brooke Cowan, Wade Shen, Christine Moran, Richard Zens, Chris Dyer, Ondrej Bojar, Alexandra Constantin, and Evan ... See full document
7
Regularized Training Objective for Continued Training for Domain Adaptation in Neural Machine Translation
... tween 4.0 and 5.3 BLEU points. Our regulariza- tion method provides additional improvement over continued training by up to to 1.5 BLEU. There is one setting (En-De Ted) where there is no change. We also repeat the ... See full document
9
Overcoming Catastrophic Forgetting During Domain Adaptation of Neural Machine Translation
... for domain adaptation in neural machine transla- ...(EWC)—a machine learning method for learning a new task without for- getting previous ...in- domain performance, outperforming ... See full document
7
Incremental Domain Adaptation for Neural Machine Translation in Low Resource Settings
... reduces translation cost and time by ...(i) Domain mismatch: the genre of samples of MEDAR dataset is signif- icantly different from the domain of the samples observed in M gen (Almahairi et ... See full document
10
Domain Adaptation and Attention Based Unknown Word Replacement in Chinese to Japanese Neural Machine Translation
... Table 3 shows two examples of the translated sentences which include unknown words, and for each example, its reference translation (R.) and its translation result (T.) are shown. The replaced unknown words ... See full document
9
Unsupervised Domain Adaptation for Neural Machine Translation with Domain Aware Feature Embeddings
... While neural machine translation (NMT) sys- tems have proven to be effective in scenarios where large amounts of in-domain data are avail- able (Gehring et ...test domain does not match ... See full document
6
Multi Domain Neural Machine Translation through Unsupervised Adaptation
... multi-domain translation scenarios call for infrastructures based on multi- ple specialised systems, each of which is tuned to maximise performance in a given ...i) domain-specific models can only be ... See full document
11
Document Level Adaptation for Neural Machine Translation
... adapt machine translation systems to novel domains, but even a well-adapted system may be able to perform better on a particular document if it were to learn from a translator’s cor- rections within the ... See full document
10
Domain and Dialect Adaptation for Machine Translation into Egyptian Arabic
... chine translation (Zbib et ...for instance, over one-third of Levantine verbs cannot be analyzed using an MSA morphological analyzer (Habash and Ram- bow, ... See full document
11
Effective Domain Mixing for Neural Machine Translation
... source domain and finetune on target-domain ...ate domain adaptation methods and propose mixing source and target domain data during ...new domain and perform well on only the ... See full document
9
Domain Adaptive Inference for Neural Machine Translation
... ensemble weighting for Neural Machine Translation, addressing the case of improving performance on a new and potentially unknown domain without sac- rificing performance on the original ... See full document
7
Non Parametric Adaptation for Neural Machine Translation
... We make two major technical contributions in this work which enable us to improve the quality of semi-parametric NMT on broad domain datasets. First, we propose using n-gram retrieval, with standard Inverse ... See full document
11
Simple, Scalable Adaptation for Neural Machine Translation
... for domain adaptation in Section ...during adaptation, but we use the adaptation stage to improve perfor- mance on languages learnt during ... See full document
11
Freezing Subnetworks to Analyze Domain Adaptation in Neural Machine Translation
... out-of- domain model, in the sense that random pertur- bations of the same magnitude cause only small performance drops on the out-of-domain test ... See full document
9
Extreme Adaptation for Personalized Neural Machine Translation
... Domain adaptation techniques for MT often rely on data selection (Moore and Lewis, 2010; Li et ...adding domain tags to NMT input (Chu et ...baseline adaptation strategy of tuning all ... See full document
7
Combining Statistical Machine Translation and Translation Memories with Domain Adaptation
... contrast, weighting the translation models (weighted TM mode) leads to a significant im- provement of all scores in both language pairs (all at p ≤ ...out-of-domain translation models is a ... See full document
11
Domain Control for Neural Machine Translation
... Machine translation systems are very sen- sitive to the domains they were trained ...Several domain adaptation techniques have already been deeply ...for neural ma- chine ... See full document
7
Domain Differential Adaptation for Neural Machine Translation
... out-of- domain data and then select data that are similar to in-domain text based on the resulting scores, a paradigm adapted by Duh et ...perform adaptation for NMT by re- trieving sentences or ... See full document
11
Sentence Embedding for Neural Machine Translation Domain Adaptation
... Recently, Neural Machine Translation (NMT) has set new state-of-the-art benchmarks on many translation tasks (Cho et ...related- domain corpora tend to have a positive impact on NMT ... See full document
7
Discriminative Instance Weighting for Domain Adaptation in Statistical Machine Translation
... for instance-weighting phrase pairs in an out-of-domain corpus in order to improve in-domain ...and instance-feature weights are learned at the same time using an efficient ... See full document
9
Related subjects