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/going-doer/paper2code
https://github.com/goldenbili/Bert_Test2
https://github.com/goldenbili/Bert_Test3
https://github.com/goldenbili/bert_lamb_pretrain
https://github.com/goodluck4s/bert-
https://github.com/google-deepmind/xquad
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/google-research-datasets/eth_py150_open
https://github.com/google-research-datasets/gap-coreference
Mind the GAP: A Balanced Corpus of Gendered Ambiguous Pronouns
https://github.com/google-research-datasets/wiki-reading
WikiReading: A Novel Large-scale Language Understanding Task over Wikipedia
https://github.com/google-research/babelcode
https://github.com/google-research/bigbird
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/google/flax/tree/master/examples/wmt
https://github.com/google/seqio
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/gooofy/zbrain
https://github.com/gooppe/transformer-summarization
https://github.com/gordicaleksa/pytorch-original-transformer
https://github.com/gouwenrui/cpe-pro-main
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/graison-thomas/TinyFinBERT
TinyBERT: Distilling BERT for Natural Language Understanding
https://github.com/graykode/gpt-2-Pytorch
https://github.com/graykode/nlp-tutorial
https://github.com/gregdurrett/nlp-qa-finalproj
ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators
https://github.com/guillaume-chevalier/Linear-Attention-Recurrent-Neural-Network
https://github.com/guoyaohua/BERT-Chinese-Annotation
https://github.com/guoyaohua/BERT-Classifier
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/guzhang480/Google_BERT
https://github.com/h4ste/oscar
https://github.com/habibullah-araphat/BERT-GPU
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/habibullah-araphat/BERT-NER-TPU
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/hackobi/AI-based-chatbot
https://github.com/haidershaour/bert
https://github.com/halo090770/bert
https://github.com/hamil168/Chatbots
https://github.com/han-shi/SparseBERT
https://github.com/hannibal046/nanorwkv
https://github.com/hans/nn-decoding
Linking artificial and human neural representations of language
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.