https://github.com/andreeaiana/newsreclib
MIND Your Language: A Multilingual Dataset for Cross-lingual News Recommendation
Papers with Code 아카이브
Cross-Lingual
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Cross-lingual natural language processing is the task of using data and models available for one language for which ample such resources are available (e.g., English) to solve tasks in another, commonly more low-resource, language.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/ant-louis/xm-retrievers
https://github.com/apple/ml-mkqa
https://github.com/ashwanitanwar/nmt-transfer-learning-xlm-r
https://github.com/atreyasha/semantic-isometry-nmt
https://github.com/bcaitech1/p2-klue-Heeseok-Jeong
https://github.com/birshert/CodeSwitchingAdversarial
Call Larisa Ivanovna: Code-Switching Fools Multilingual NLU Models
https://github.com/bitextor/bicleaner-ai
https://github.com/cair/PyTsetlinMachineCUDA
Explainable Tsetlin Machine framework for fake news detection with credibility score assessment
https://github.com/cair/TsetlinMachine
Explainable Tsetlin Machine framework for fake news detection with credibility score assessment
https://github.com/cair/pyTsetlinMachine
Explainable Tsetlin Machine framework for fake news detection with credibility score assessment
https://github.com/cair/pyTsetlinMachineMT
Explainable Tsetlin Machine framework for fake news detection with credibility score assessment
https://github.com/cair/pyTsetlinMachineParallel
Explainable Tsetlin Machine framework for fake news detection with credibility score assessment
https://github.com/ckinateder/pytsetlinmachineparallel
Explainable Tsetlin Machine framework for fake news detection with credibility score assessment
https://github.com/deepmind/xquad
https://github.com/deepset-ai/FARM
https://github.com/deterministic-algorithms-lab/Large-XLM
https://github.com/edchengg/transfusion
Frustratingly Easy Label Projection for Cross-lingual Transfer
https://github.com/epfml/sent2vec
https://github.com/eske/multivec
BilBOWA: Fast Bilingual Distributed Representations without Word Alignments
https://github.com/eternityyw/tram-benchmark
https://github.com/ezelikman/STaR
ZeRO: Memory Optimizations Toward Training Trillion Parameter Models
https://github.com/facebookresearch/data2vec_vision
InfoXLM: An Information-Theoretic Framework for Cross-Lingual Language Model Pre-Training
https://github.com/facebookresearch/fairscale
ZeRO: Memory Optimizations Toward Training Trillion Parameter Models
https://github.com/facebookresearch/fairseq
Simple and Effective Zero-shot Cross-lingual Phoneme Recognition
https://github.com/facebookresearch/vissl
ZeRO: Memory Optimizations Toward Training Trillion Parameter Models
https://github.com/facebookresearch/vizseq
Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyond
https://github.com/fajri91/indommlu
https://github.com/feyzaakyurek/XLM-LwLL
https://github.com/galsang/galsang
Don't Just Scratch the Surface: Enhancing Word Representations for Korean with Hanja
https://github.com/google-deepmind/xquad
https://github.com/heraclex12/vietpunc
https://github.com/htanwar922/Language-Adversarial-Network
Adversarial Deep Averaging Networks for Cross-Lingual Sentiment Classification
https://github.com/huchen365/ds
ZeRO: Memory Optimizations Toward Training Trillion Parameter Models
https://github.com/huggingface/transformers
https://github.com/huggingface/transformers/tree/master/src/transformers/models/byt5
ByT5: Towards a token-free future with pre-trained byte-to-byte models
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.