Papers with Code 아카이브
NMT
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 1
- 평가표
- 0
- 보존된 평가 기록
- 0
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/hukuda222/code2seq
code2seq: Generating Sequences from Structured Representations of Code
https://github.com/huulinhcvp/chatBot
Effective Approaches to Attention-based Neural Machine Translation
https://github.com/ijauregiCMCRC/ReWE_NMT
Stronger Baselines for Trustable Results in Neural Machine Translation
https://github.com/ikergarcia1996/easy-label-projection
https://github.com/inmoonlight/confcrawl
Why Skip If You Can Combine: A Simple Knowledge Distillation Technique for Intermediate Layers
https://github.com/insigh/THUMT
THUMT: An Open Source Toolkit for Neural Machine Translation
https://github.com/ipieter/universal-distillation
https://github.com/isi-nlp/Zoph_RNN
Transfer Learning for Low-Resource Neural Machine Translation
https://github.com/isl-mt/OpenNMT
https://github.com/jackjhliu/End-to-End-Mandarin-ASR
Effective Approaches to Attention-based Neural Machine Translation
https://github.com/jackjhliu/Pytorch-End-to-End-ASR-on-TIMIT
Effective Approaches to Attention-based Neural Machine Translation
https://github.com/jarl93/joeynmt-modified
https://github.com/jeongukjae/smaller-labse
https://github.com/jmyrberg/finnlem
Effective Approaches to Attention-based Neural Machine Translation
https://github.com/johnr0/TaleBrush-backend
https://github.com/josephch405/curriculum-nmt
Improving Neural Machine Translation Models with Monolingual Data
https://github.com/juliakreutzer/bandit-neuralmonkey
https://github.com/juliakreutzer/joeynmt
https://github.com/jungokasai/twist_decoding
Domain Adaptation of Neural Machine Translation by Lexicon Induction
https://github.com/junjiehu/dali
Domain Adaptation of Neural Machine Translation by Lexicon Induction
https://github.com/jwieting/beyond-bleu
Beyond BLEU: Training Neural Machine Translation with Semantic Similarity
https://github.com/karpathy/minbpe
https://github.com/keleog/PidginUNMT
https://github.com/keonlee9420/VAENAR-TTS
FlowSeq: Non-Autoregressive Conditional Sequence Generation with Generative Flow
https://github.com/kh-kim/simple-nmt
Effective Approaches to Attention-based Neural Machine Translation
https://github.com/kh-mo/QA_wikisql
https://github.com/khanhptnk/bandit-nmt
Effective Approaches to Attention-based Neural Machine Translation
https://github.com/kheeong/XLM_OWN
https://github.com/kmkwon94/ainize-laser
CCMatrix: Mining Billions of High-Quality Parallel Sentences on the WEB
https://github.com/kpu/intgemm
Sharp Models on Dull Hardware: Fast and Accurate Neural Machine Translation Decoding on the CPU
https://github.com/ksulima/Unsupervised-method-to-NPL-Polish-language
https://github.com/lancopku/SACT
https://github.com/laniqo-public/grammar-data-mtsummit25
https://github.com/ldulcic/chatbot
Effective Approaches to Attention-based Neural Machine Translation
https://github.com/liernisestorain/zero-shot-dual-MT
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.