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Low-Resource Neural Machine Translation
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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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이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Language Model Prior for Low-Resource Neural Machine Translation
Low Resource Neural Machine Translation: A Benchmark for Five African Languages
A Survey of Methods to Leverage Monolingual Data in Low-resource Neural Machine Translation
A Universal Parent Model for Low-Resource Neural Machine Translation Transfer
Improving Back-Translation with Uncertainty-based Confidence Estimation
Exploiting Out-of-Domain Parallel Data through Multilingual Transfer Learning for Low-Resource Neural Machine Translation
Revisiting Low-Resource Neural Machine Translation: A Case Study
Corpus Augmentation by Sentence Segmentation for Low-Resource Neural Machine Translation
Target Conditioned Sampling: Optimizing Data Selection for Multilingual Neural Machine Translation
Effective Cross-lingual Transfer of Neural Machine Translation Models without Shared Vocabularies
Bi-Directional Differentiable Input Reconstruction for Low-Resource Neural Machine Translation
Trivial Transfer Learning for Low-Resource Neural Machine Translation
Meta-Learning for Low-Resource Neural Machine Translation
Data Augmentation for Low-Resource Neural Machine Translation
Transfer Learning for Low-Resource Neural Machine Translation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.