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NMT
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Neural machine translation is an approach to machine translation that uses an artificial neural network to predict the likelihood of a sequence of words, typically modeling entire sentences in a single integrated model.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/stanford-oval/SPL
공식 코드Localizing Open-Ontology QA Semantic Parsers in a Day Using Machine Translation
https://github.com/steventan0110/NMTModelAttack
공식 코드Doubly-Trained Adversarial Data Augmentation for Neural Machine Translation
https://github.com/su0315/discourse_context_mt
공식 코드Context-aware Neural Machine Translation for English-Japanese Business Scene Dialogues
https://github.com/sunbowliu/ptvsbt
공식 코드On the Complementarity between Pre-Training and Back-Translation for Neural Machine Translation
https://github.com/surafelml/Afro-NMT
공식 코드Low Resource Neural Machine Translation: A Benchmark for Five African Languages
https://github.com/surafelml/adapt-mnmt
공식 코드Adapting Multilingual Neural Machine Translation to Unseen Languages
https://github.com/suralk/multiner
공식 코드A Multi-way Parallel Named Entity Annotated Corpus for English, Tamil and Sinhala
https://github.com/tanggongbo/negation-evaluation-nmt
공식 코드https://github.com/tanggongbo/normalization-NMT
공식 코드An Evaluation of Neural Machine Translation Models on Historical Spelling Normalization
https://github.com/tartunlp/inherent-domains-wmt21
공식 코드https://github.com/tech-srl/code2seq
공식 코드code2seq: Generating Sequences from Structured Representations of Code
https://github.com/tempra28/nmtrnng
공식 코드Learning to Parse and Translate Improves Neural Machine Translation
https://github.com/tempra28/tree2seq
공식 코드https://github.com/thammegowda/005-nmt-imbalance
공식 코드Finding the Optimal Vocabulary Size for Neural Machine Translation
https://github.com/thompsonb/prism
공식 코드Automatic Machine Translation Evaluation in Many Languages via Zero-Shot Paraphrasing
https://github.com/thunlp-mt/ckd
공식 코드Continual Knowledge Distillation for Neural Machine Translation
https://github.com/thunlp-mt/template-nmt
공식 코드A Template-based Method for Constrained Neural Machine Translation
https://github.com/thunlp-mt/transformer-dmb
공식 코드Dynamic Multi-Branch Layers for On-Device Neural Machine Translation
https://github.com/tjunlp-lab/pckmt
공식 코드Efficient Cluster-Based k-Nearest-Neighbor Machine Translation
https://github.com/toshohirasawa/nmtpytorch-emb-pred
공식 코드https://github.com/trangvu/guda
공식 코드https://github.com/trusthlt/dp-nmt
공식 코드https://github.com/trusthlt/granularity-is-crucial-dp
공식 코드https://github.com/turkic-interlingua/til-mt
공식 코드Evaluating Multiway Multilingual NMT in the Turkic Languages
https://github.com/tuzhaopeng/LC-NMT
공식 코드Exploiting Cross-Sentence Context for Neural Machine Translation
https://github.com/tuzhaopeng/NMT-Coverage
공식 코드https://github.com/tuzhaopeng/nmt
공식 코드https://github.com/uds-lsv/3st
공식 코드Exploiting Social Media Content for Self-Supervised Style Transfer
https://github.com/utsjiyaoli/qa-attack
공식 코드Deceiving Question-Answering Models: A Hybrid Word-Level Adversarial Approach
https://github.com/vernadankers/mt_idioms
공식 코드Can Transformer be Too Compositional? Analysing Idiom Processing in Neural Machine Translation
https://github.com/victorwz/zs-nmt-dae
공식 코드Rethinking Zero-shot Neural Machine Translation: From a Perspective of Latent Variables
https://github.com/violet-zct/pytorch-reorder-nmt
공식 코드Handling Syntactic Divergence in Low-resource Machine Translation
https://github.com/vman049/MultilingualLexicalSemantics
공식 코드How do lexical semantics affect translation? An empirical study
https://github.com/vyraun/finding-memo
공식 코드Finding Memo: Extractive Memorization in Constrained Sequence Generation Tasks
https://github.com/vyraun/hallucinations
공식 코드The Curious Case of Hallucinations in Neural Machine Translation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.