https://github.com/venkyr91193/Sentiment_Analysis_with_BERT
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
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- 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/vgupta123/Unsupervised-SAS
https://github.com/vid-koci/weightingGAP
Mind the GAP: A Balanced Corpus of Gendered Ambiguous Pronouns
https://github.com/vijay120/bert
https://github.com/vikashranjan/transformer
https://github.com/vinairesearch/phogpt
https://github.com/vinayprabhu/X-is-all-you-need
https://github.com/viniciusoliveirasd/bert-applications
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/vishnuanil122/Bert-Binary-Text-Classifier
https://github.com/vivekgohel56/Neural-machine-translation-english-to-polish
https://github.com/vmware-labs/bert-pretraining
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/volcengine/vegiantmodel
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/vpj/jax_transformer
https://github.com/vulus98/rethinking-attention
https://github.com/vvvm23/TchAIkovsky-Legacy
https://github.com/walkacross/transformer-pytorch
https://github.com/wangcongcong123/ttt
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/wangcunxiang/SemEval2020-Task4-Commonsense-Validation-and-Explanation
Does It Make Sense? And Why? A Pilot Study for Sense Making and Explanation
https://github.com/wangmz15/Chinese-Error-Correction-with-THUMT
https://github.com/wayalhruhi/gogle_bert
https://github.com/wchh127/yykf
https://github.com/weidafeng/NLU2019
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/wenhuchen/HDSA-Dialog
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/whqwill/seq2seq-keyphrase-bert
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/whr94621/NJUNMT-pytorch
https://github.com/why2000/DuReader-bert
https://github.com/writerai/fitbert
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/wxt1997/Transformer-Transducer
https://github.com/wyf-python/Bert-Pytorch-TextClassification
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/wzlxjtu/PositionalEncoding2D
https://github.com/wzzzd/LM_NER
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/wzzzd/Pretrain_Bert_with_MaskLM
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/xbtlin/All-about-Machine-Learning
https://github.com/xcmyz/FastSpeech
https://github.com/xesdiny/test-bert-master
https://github.com/xiangyue9607/CliniRC
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.