Papers with Code 아카이브
Natural Language Understanding
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
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- 평가표
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- 보존된 평가 기록
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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/YuehChuan/bert-Agus
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/YunwenTechnology/Unilm
Unified Language Model Pre-training for Natural Language Understanding and Generation
https://github.com/YvanG/VQGAN-CLIP
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/ZackPashkin/text2cartoon-pytorch-CLIP
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/Zeeshan75/Bert_Telugu_Ner
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/Zehui127/SQUAD_BERT
https://github.com/ZmeiGorynych/transformer_pytorch
https://github.com/ZurichNLP/sockeye
https://github.com/a414351664/Bert_MRC
https://github.com/a736875071/clip-vit-large-patch14
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/aaronH45/sentimentAnalysis
https://github.com/aaronHuang0121/AI-CUP-2020
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/aau-es-ml/ssl_noise-robust_kws
data2vec: A General Framework for Self-supervised Learning in Speech, Vision and Language
https://github.com/abcp4/DAPytorch
https://github.com/abhaskumarsinha/Keras-implementation-of-Transformer-Architecture
https://github.com/abhaskumarsinha/Keras-implementation-of-Transformer-Architecture/blob/main/Transformer.py
https://github.com/abhaskumarsinha/MinimalGPT
https://github.com/abhiagg92/bert_sentiment
https://github.com/abhilash1910/BERTSimilarity
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/abhilashreddys/Fake-News-Article
https://github.com/abhilashreddys/infoADAPET
It's Not Just Size That Matters: Small Language Models Are Also Few-Shot Learners
https://github.com/abhineet/sentence_classification_pubmed_scibert
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/abmitra84/Language_Modeling
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/abmitra84/Machine_Translation
https://github.com/adi2103/AML-CoVe
https://github.com/adlnlp/Midas
MIDAS: Multi-level Intent, Domain, And Slot Knowledge Distillation for Multi-turn NLU
https://github.com/af-ai-center/bert
https://github.com/af-ai-center/nerblackbox
https://github.com/agentdr1/la_mil
https://github.com/ahmedssabir/Textual-Visual-Semantic-Dataset-for-Text-Spotting
Visual Re-ranking with Natural Language Understanding for Text Spotting
https://github.com/ahmedssabir/dataset
Visual Re-ranking with Natural Language Understanding for Text Spotting
https://github.com/ahmetumutdurmus/awd-lstm
https://github.com/ahsanabbas123/Transformer
https://github.com/ai-agi/hicl
https://github.com/ai-forever/ru-clip
Learning Transferable Visual Models From Natural Language Supervision
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.