Papers with Code 아카이브
Multimodal Machine Translation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
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- 평가표
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- 보존된 평가 기록
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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.
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https://github.com/yiyc-kor/bert-study
https://github.com/ykrmm/ICLR_2020
https://github.com/ykrmm/TREMBA
https://github.com/yoongtr/Grammar-Error-Correction-with-OpenNMT-tf
https://github.com/ypeleg/MinimalIsAllYouNeed
https://github.com/yuanmu97/secure-transformer-inference
https://github.com/yueyongjiao/Transformer-Contextual
https://github.com/yueyongjiao/attention_is_all_you_need_pytorch
https://github.com/yuhangT/tf_bert
https://github.com/yumoh/speech-keras
https://github.com/yydai/bert_test
https://github.com/zankner/Transformer
https://github.com/zapplea/bert
https://github.com/zer0sh0t/artificial_intelligence/tree/master/transformer
https://github.com/zhang-huihui/git-repository
https://github.com/zhangbo2008/best_pytorch_transformer
https://github.com/zipeiyang/DeepSpeechRecognition
https://github.com/zsweet/BERT_zsw
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출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.