Low-Resource Neural Machine Translation
Low-resource machine translation is the task of machine translation on a low-resource language where large data may not be available.
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Transfer Learning for Low-Resource Neural Machine Translation
Ensembling and unknown word replacement add another 2 Bleu which brings the NMT performance on low-resource machine translation close to a strong syntax based machine translation (SBMT) system, exceeding its performance on one language pair.
Data Augmentation for Low-Resource Neural Machine Translation
ACL 2017
• marziehf/DataAugmentationNMT
• 
The quality of a Neural Machine Translation system depends substantially on the availability of sizable parallel corpora.
Exploiting Out-of-Domain Parallel Data through Multilingual Transfer Learning for Low-Resource Neural Machine Translation
This paper proposes a novel multilingual multistage fine-tuning approach for low-resource neural machine translation (NMT), taking a challenging Japanese--Russian pair for benchmarking.
DOMAIN ADAPTATION LOW-RESOURCE NEURAL MACHINE TRANSLATION TRANSFER LEARNING
Effective Cross-lingual Transfer of Neural Machine Translation Models without Shared Vocabularies
ACL 2019
• yunsukim86/sockeye-transfer
• 
Transfer learning or multilingual model is essential for low-resource neural machine translation (NMT), but the applicability is limited to cognate languages by sharing their vocabularies.
CROSS-LINGUAL TRANSFER LOW-RESOURCE NEURAL MACHINE TRANSLATION TRANSFER LEARNING
Improving Low-Resource Neural Machine Translation with Filtered Pseudo-Parallel Corpus
Large-scale parallel corpora are indispensable to train highly accurate machine translators.
Revisiting Low-Resource Neural Machine Translation: A Case Study
It has been shown that the performance of neural machine translation (NMT) drops starkly in low-resource conditions, underperforming phrase-based statistical machine translation (PBSMT) and requiring large amounts of auxiliary data to achieve competitive results.