https://github.com/mirbostani/QA-KD-AL
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Papers with Code 아카이브
Natural Language Understanding
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 2
- 평가표
- 6
- 보존된 평가 기록
- 42
Natural Language Understanding is an important field of Natural Language Processing which contains various tasks such as text classification, natural language inference and story comprehension. Applications enabled by natural language understanding range from question answering to automated reasoning.
Source: Find a Reasonable Ending for Stories: Does Logic Relation Help the Story Cloze Test?
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/mithunpaul08/bert_tensorflow
https://github.com/mitran27/Attention-is-all-you-Need
https://github.com/mkavim/finetune_bert
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/ml-jku/cloob
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/mlbio-epfl/turtle
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/mlfoundations/dclm
DataComp-LM: In search of the next generation of training sets for language models
https://github.com/mlfoundations/open_clip
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/mocherson/aki_bert
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/moein-shariatnia/Pix2Seq
https://github.com/mohamedateya/bert-fine-tuning-sentence-classification-for-cola
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/monimoyd/NLPEnglishToPythonCodeUsingTransformer
https://github.com/monimoyd/NLPMachineTranslationUsingTransformer
https://github.com/monologg/JointBERT
https://github.com/moon23k/Scheduled_Sampling
https://github.com/moon23k/Transformer_Anchors
https://github.com/moon23k/Transformer_Archs
https://github.com/morganmcg1/reformer-fastai
AutoTrans: Automating Transformer Design via Reinforced Architecture Search
https://github.com/morganmcg1/reformer-fastai-old
AutoTrans: Automating Transformer Design via Reinforced Architecture Search
https://github.com/moussaKam/OrangeSum
BARThez: a Skilled Pretrained French Sequence-to-Sequence Model
https://github.com/mtzcorporations/nlp_teamjodka
https://github.com/musixmatchresearch/umberto
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/muzairkhattak/multimodal-prompt-learning
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/myamamoto555/tf-bert
https://github.com/mzakizadeh/Gender-Encoding-Patterns
Debiasing Methods in Natural Language Understanding Make Bias More Accessible
https://github.com/nachiketaa/BERT-pytorch
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/nachiketaa/bert
https://github.com/nageshsinghc4/deepwrap
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/nahidalam/open_clip
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/nalbarr/coursera-ai4med-course3
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/nameoverflow/neuro-cangjie
https://github.com/natel9178/transformer-refork
https://github.com/nathanlesage/so-classifier
https://github.com/neburseni/NLP
https://github.com/nelson-liu/lexical-semantic-recognition
https://github.com/neqkir/attention-mechanism
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.