Papers with Code 아카이브
Multimodal Machine Translation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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Multimodal machine translation is the task of doing machine translation with multiple data sources - for example, translating "a bird is flying over water" + an image of a bird over water to German text.
<span style="color:grey; opacity: 0.6">( Image credit: Findings of the Third Shared Task on Multimodal Machine Translation )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/EugeneSel/EUMT
https://github.com/EuphoriaYan/bert_component
https://github.com/Eurus-Holmes/VAG-NMT
A Visual Attention Grounding Neural Model for Multimodal Machine Translation
https://github.com/FaskyCC/TextClassification
https://github.com/FengJiaChunFromSYSU/Bert
https://github.com/FlorianPfisterer/2D-LSTM-Seq2Seq
https://github.com/Fuchai/language
https://github.com/G-4-R-Y/Tweet-Sentiment-Extraction
https://github.com/G-4-R-Y/Tweet-Sentiment-Extraction-roBERTa-5fold
https://github.com/Gaozhen0816/BERT_QA_For_AILaw
https://github.com/Gaozhen0816/BERT_QA_for_Chinese
https://github.com/Glaceon31/Document-Transformer
https://github.com/GlassyWing/transformer-keras
https://github.com/HKUST-KnowComp/R-Net
https://github.com/HanhaiNotHai/transformer
https://github.com/Harry-Muzart/harry-muzart.github.io
https://github.com/Helsinki-NLP/shared-info
https://github.com/HeshamElAbd/SelfAttentionLangModel
https://github.com/HzcIrving/DeepLearning_PlayGround
https://github.com/IBM/pytorch-seq2seq
https://github.com/IOB-Muenster/TEclass2
https://github.com/IrishCoffee/cudnnMultiHeadAttention
https://github.com/Iwontbecreative/Abstractive-summarization-OpenNMT
https://github.com/Izecson/saml-nmt
https://github.com/Izecson/sockeye-1.16.6
https://github.com/JNUpython/bert
https://github.com/JRC1995/Machine-Translation-Transformers
https://github.com/JanAthmer/Compositional-generalization-capabillity-of-Transformer
https://github.com/JeheonPark596/sentimentsurvival
https://github.com/JohannLee1996/bert
https://github.com/Joshuaoneheart/Fintech-Final-Report
https://github.com/Katsumata420/bert_mlm
https://github.com/KeithGalli/pycon2020
https://github.com/Kevin-Vora/bert-embedding-gluonnlp-edit-
https://github.com/Khalid-Jamal/annotated-transformer-Arabic
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.