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/HanhaiNotHai/transformer
https://github.com/Harry-Muzart/harry-muzart.github.io
https://github.com/HarshitaSahai/conversational-agent
Collaborative Multi-Agent Dialogue Model Training Via Reinforcement Learning
https://github.com/Helsinki-NLP/shared-info
https://github.com/HeshamElAbd/SelfAttentionLangModel
https://github.com/Hibb-bb/ALLM
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/Holldean/BERT-Pruning
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/Huawei-MRC-OSI/mrc-nlp-public
https://github.com/HuihuiChyan/BJTUNLP_Practice2020
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/HuihuiChyan/BJTUNLP_Practice2021
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/HzcIrving/DeepLearning_PlayGround
https://github.com/IBM/ColBERT-practical
ColBERT: Efficient and Effective Passage Search via Contextualized Late Interaction over BERT
https://github.com/IBM/MAX-Question-Answering
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/IBM/MAX-Text-Sentiment-Classifier
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/IBM/MAX-Toxic-Comment-Classifier
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/IBM/pytorch-seq2seq
https://github.com/IMPLabUniPr/UniParma-at-semeval-2021-task-5
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/IMvision12/keras-vision-models
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/IOB-Muenster/TEclass2
https://github.com/Impavidity/relogic
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/IndicoDataSolutions/finetune
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/IrishCoffee/cudnnMultiHeadAttention
https://github.com/Iwontbecreative/Abstractive-summarization-OpenNMT
https://github.com/Izecson/saml-nmt
https://github.com/Izecson/sockeye-1.16.6
https://github.com/JA-Bar/nlp-depression
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/JMSaindon/NlpSquad
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/JNUpython/bert
https://github.com/JONGWE1/Paddle-DeBERTa
https://github.com/JRC1995/Machine-Translation-Transformers
https://github.com/Jackma3/NER-Bert-BiLstm
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/JanAthmer/Compositional-generalization-capabillity-of-Transformer
https://github.com/Jason-J-Choi/DeBERTa_TxtClassifier
https://github.com/JeheonPark596/sentimentsurvival
https://github.com/JoegameZhou/mPanGu-Alpha-53
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.