Papers with Code 아카이브
Joint Multilingual Sentence Representations
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/goodbai-nlp/amrbart
https://github.com/imamathcat/LASER_Dependencies
Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyond
https://github.com/jeongukjae/smaller-labse
Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyond
https://github.com/jiamingkong/infoxlm_paddle
Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyond
https://github.com/kmkwon94/ainize-laser
Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyond
https://github.com/laiviet/ConvAMR-torch
ConvAMR: Abstract meaning representation parsing for legal document
https://github.com/mdtux89/amr-eager
https://github.com/pournaki/transition-amr-parser
Inducing and Using Alignments for Transition-based AMR Parsing
https://github.com/prabhakar267/LASER-improved
Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyond
https://github.com/raymondhs/fairseq-laser
Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyond
https://github.com/shibhansh/Unsupervised-SAS
https://github.com/summarization/semantic_summ
Toward Abstractive Summarization Using Semantic Representations
https://github.com/transducens/LASERtrain
Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyond
https://github.com/vgupta123/Unsupervised-SAS
https://github.com/yannvgn/laserembeddings
Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyond
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.