Papers with Code 아카이브
Multimodal Machine Translation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 2
- 평가표
- 3
- 보존된 평가 기록
- 17
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/camlaedtke/NLP
https://github.com/caoyujiALgLM/NLP
https://github.com/caoyujiALgLM/NLP-progress
https://github.com/chalothon/BERT_Practice
https://github.com/chandu7077/mybert
https://github.com/chen-xiong-yi/OwnBERT
https://github.com/chengchingwen/transformers.jl
https://github.com/chiayewken/bert-qa
https://github.com/chrisleunglokhin/Capstone-BERT
https://github.com/christianspybrook/article_recommender
https://github.com/cloudmcloudyo/capstone
https://github.com/cmsflash/efficient-attention
https://github.com/coco60/bert-test
https://github.com/colorfulscoop/tfdlg
https://github.com/conceptofmind/LaMDA-pytorch
https://github.com/conceptofmind/lamda-rlhf-pytorch
https://github.com/coronazap/bert_client
https://github.com/cosmoquester/seq2seq
https://github.com/cospplay/bert-master
https://github.com/coxy1989/tfmr
https://github.com/cpm0722/transformer_pytorch
https://github.com/cuber2460/bert
https://github.com/cyberzhg/keras-pos-embd
https://github.com/czero69/acomoeye-NN
https://github.com/davidalbertonogueira/NLP-tutorials
https://github.com/davisking/dlib-models
https://github.com/dccuchile/CC6204
https://github.com/deepmind/haiku
https://github.com/deepmipt/bert/tree/feat/multi_gpu
https://github.com/demelin/nematode
https://github.com/derylucio/Transformer
https://github.com/dhiraa/tener
https://github.com/dl-nlp/dl-nlp.github.io
https://github.com/dmlc/gluon-nlp
https://github.com/dqqcasia/st
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.