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Low Resource Neural Machine Translation

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코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/Mao-KU/JASS

공식 코드

Linguistically-driven Multi-task Pre-training for Low-resource Neural Machine Translation

https://github.com/NLP2CT/Meta-Curriculum

공식 코드

Meta-Curriculum Learning for Domain Adaptation in Neural Machine Translation

https://github.com/THUNLP-MT/UCE4BT

공식 코드

Improving Back-Translation with Uncertainty-based Confidence Estimation

https://github.com/aliaraabi/joint_dropout

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Joint Dropout: Improving Generalizability in Low-Resource Neural Machine Translation through Phrase Pair Variables

https://github.com/alimrsn79/da_lr_nmt

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From Priest to Doctor: Domain Adaptaion for Low-Resource Neural Machine Translation

https://github.com/anzeyimana/kinmt_naacl2024

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Low-resource neural machine translation with morphological modeling

https://github.com/cbaziotis/lm-prior-for-nmt

공식 코드

Language Model Prior for Low-Resource Neural Machine Translation

https://github.com/ictnlp/lnmt-ca

공식 코드

Low-resource Neural Machine Translation with Cross-modal Alignment

https://github.com/marian-nmt/marian

공식 코드

Approaching Neural Chinese Word Segmentation as a Low-Resource Machine Translation Task

https://github.com/marziehf/DataAugmentationNMT

공식 코드

Data Augmentation for Low-Resource Neural Machine Translation

https://github.com/nlp2ct/consisttl

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ConsistTL: Modeling Consistency in Transfer Learning for Low-Resource Neural Machine Translation

https://github.com/surafelml/Afro-NMT

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Low Resource Neural Machine Translation: A Benchmark for Five African Languages

https://github.com/suralk/multiner

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A Multi-way Parallel Named Entity Annotated Corpus for English, Tamil and Sinhala

https://github.com/transducens/mtl-da-emnlp

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Rethinking Data Augmentation for Low-Resource Neural Machine Translation: A Multi-Task Learning Approach

https://github.com/xingniu/sockeye

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Bi-Directional Differentiable Input Reconstruction for Low-Resource Neural Machine Translation

https://github.com/yunsukim86/sockeye-transfer

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Effective Cross-lingual Transfer of Neural Machine Translation Models without Shared Vocabularies

https://github.com/zanchangtong/ptvsri

공식 코드

On the Complementarity between Pre-Training and Random-Initialization for Resource-Rich Machine Translation

https://github.com/aizhanti/jarunc

Exploiting Out-of-Domain Parallel Data through Multilingual Transfer Learning for Low-Resource Neural Machine Translation

https://github.com/ewdowiak/Sicilian_Translator

Revisiting Low-Resource Neural Machine Translation: A Case Study

https://github.com/isi-nlp/Zoph_RNN

Transfer Learning for Low-Resource Neural Machine Translation

https://github.com/yuekai146/NMT

Revisiting Low-Resource Neural Machine Translation: A Case Study

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.