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/MS-Mind/MS-Code-01/tree/main/soft_masked_bert
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/MS-P3/code5/tree/main/bert
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/MS-P3/code5/tree/main/llama3
An empirical study of LLaMA3 quantization: from LLMs to MLLMs
https://github.com/MS-P3/code7/tree/main/vision_text_dual_encoder
https://github.com/MS-P3/code7/tree/main/xlm
https://github.com/MS-P3/code7/tree/main/xlm_roberta
https://github.com/MaZhiyuanBUAA/bert-tf1.4.0
https://github.com/MahmoudWahdan/dialog-nlu
https://github.com/MalteHB/-l-ctra
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/ManasRMohanty/DS5500-capstone
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/MansMeg/IntroML
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/Maple728/transformer
https://github.com/MarcBS/keras
https://github.com/MarcosGrzeca/drunktweets
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/MashaKubyshina/learning_ML
https://github.com/MatthewSwahn/news-headlines-sarcasm-detector
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/Matthewdowney18/Transformer_Dialogue
https://github.com/Maz101/Bert
https://github.com/Maz101/pretrainingdataset
https://github.com/MichaelZhouwang/LMlexsub
https://github.com/Microsoft/AzureML-BERT
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/Microsoft/nail_agent
https://github.com/Mind23-2/MindCode-133
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/Mind23-2/MindCode-144
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/Mind23-2/MindCode-145
NEZHA: Neural Contextualized Representation for Chinese Language Understanding
https://github.com/Mind23-2/MindCode-161
https://github.com/MindCode-4/code-3/tree/main/data2vec
data2vec: A General Framework for Self-supervised Learning in Speech, Vision and Language
https://github.com/MindCode-4/code-3/tree/main/dbrx
https://github.com/MindCode-4/code-3/tree/main/deberta
https://github.com/MindCode-4/code-3/tree/main/deberta_v2
https://github.com/MindCode-4/code-5/tree/main/tinybert
TinyBERT: Distilling BERT for Natural Language Understanding
https://github.com/MindCode-4/code-5/tree/main/transformer
https://github.com/MindSpore-paper-code-3/code9/tree/main/ernie
ERNIE 3.0: Large-scale Knowledge Enhanced Pre-training for Language Understanding and Generation
https://github.com/MindSpore-paper-code-3/code9/tree/main/soft_masked_bert
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/MindSpore-scientific-2/code-14/tree/main/gptj
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.