https://github.com/NisansaDdS/Some-Languages-are-More-Equal-than-Others
Systematic Inequalities in Language Technology Performance across the World's Languages
Papers with Code 아카이브
Machine Translation
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Machine translation is the task of translating a sentence in a source language to a different target language.
Approaches for machine translation can range from rule-based to statistical to neural-based. More recently, encoder-decoder attention-based architectures like BERT have attained major improvements in machine translation.
One of the most popular datasets used to benchmark machine translation systems is the WMT family of datasets. Some of the most commonly used evaluation metrics for machine translation systems include BLEU, METEOR, NIST, and others.
<span style="color:grey; opacity: 0.6">( Image credit: Google seq2seq )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/NonameAuPlatal/Dual_Learning
https://github.com/Nstats/bert_MRC
https://github.com/Nstats/bert_senti_analysis_ch
https://github.com/Nstats/my_bert
https://github.com/OPAYA/Transformer
https://github.com/OctopusNO1/Artificial-Intelligence-Guide
https://github.com/Oguzhanercan/Vision-Transformers
https://github.com/OpenNMT/OpenNMT-py
https://github.com/OpenNMT/OpenNMT-tf
Guided Alignment Training for Topic-Aware Neural Machine Translation
https://github.com/Osobarako/alduswarrensewell
https://github.com/PaddlePaddle/FleetX/tree/develop/examples/pipeline
GPipe: Efficient Training of Giant Neural Networks using Pipeline Parallelism
https://github.com/PaddlePaddle/PaddleNLP/tree/develop/examples/language_model/gpt-3
https://github.com/PaddlePaddle/PaddleNLP/tree/develop/examples/language_model/t5
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
https://github.com/PaddlePaddle/PaddleNLP/tree/develop/examples/machine_translation/transformer
https://github.com/PaddlePaddle/PaddleSpeech
https://github.com/PatxiofromAlphensign/subword-nmt-mods
https://github.com/PaulSudarshan/Language-Classification-Using-Naive-Bayes-Algorithm
https://github.com/Pek20180909/dp-transformer
https://github.com/Pendulibrium/ai-visual-storytelling-seq2seq
Effective Approaches to Attention-based Neural Machine Translation
https://github.com/Pezhin/best_yelp_review_project_ever
https://github.com/PranotiDesai/MachineTranslation
https://github.com/PrideLee/sentiment-analysis
https://github.com/Pruthwik/Odia-POS-Tagger
https://github.com/QAQ-v/MMT
https://github.com/QData/deepWordBug
TextAttack: A Framework for Adversarial Attacks, Data Augmentation, and Adversarial Training in NLP
https://github.com/RUCAIBox/LLMBox
https://github.com/Rami97rgb/French-to-English-Translator
https://github.com/Recognito-Vision/Android-FaceRecognition-FaceLivenessDetection
https://github.com/Remiphilius/PoemesProfonds
https://github.com/RenXiangyuan/tf_bert
https://github.com/RobustNLP/TestTranslation
https://github.com/Rudedaisy/attention-is-all-you-need-pytorch
https://github.com/SCismycat/bert_code_view
https://github.com/SFFAI-AIKT/AIKT-Natural_Language_Processing
A Survey on Document-level Neural Machine Translation: Methods and Evaluation
https://github.com/SYangDong/bert-with-frozen-code
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.