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/Joshuaoneheart/Fintech-Final-Report
https://github.com/JoyDajunSpaceCraft/RAG-RLRC-LaySum
ColBERT: Efficient and Effective Passage Search via Contextualized Late Interaction over BERT
https://github.com/Jun-Zhang-32108/Sentiment-Analysis
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/JunnYu/paddle_convbert
ConvBERT: Improving BERT with Span-based Dynamic Convolution
https://github.com/JunnYu/xlm_paddle
https://github.com/KLUE-benchmark/KLUE-baseline
https://github.com/Kanishkparganiha/Named-Entity-Recognition-using-BERT-with-PyTorch
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/Karthik-Bhaskar/Context-Based-Question-Answering
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/Katsumata420/bert_mlm
https://github.com/Kaushalya/medclip
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/KeithGalli/pycon2020
https://github.com/Kerram/Deephol-Bert-Zpp
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/Kevin-Vora/bert-embedding-gluonnlp-edit-
https://github.com/Khalid-Jamal/annotated-transformer-Arabic
https://github.com/Kirankumaraswamy/Transformers
https://github.com/KnightZhang625/BERT_TF
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/KomorebiLHX/Emotion-Recognition-in-Conversations
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/Kosuke-Szk/BERT-NER-ja
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/KrishnaTarun/Deep-Learning-Lab
https://github.com/Kyubyong/bert-token-embeddings
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/Kyubyong/transformer
https://github.com/Lackel/DNA
Benchmarking Natural Language Understanding Services for building Conversational Agents
https://github.com/Lemoners/Attention-Is-All-You-Need
https://github.com/LeoWood/bert-horovod
https://github.com/LeonZh0u/Chatbot
Unified Language Model Pre-training for Natural Language Understanding and Generation
https://github.com/LiamMaclean216/Pytorch-Chatbot
https://github.com/LiamMaclean216/Pytorch-Transfomer
https://github.com/Linar23/Research_work
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/LorenzoAgnolucci/BERT_for_ABSA
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/LoveYang/bert_test
https://github.com/Lsdefine/attention-is-all-you-need-keras
https://github.com/MARIO-Math-Reasoning/Super_MARIO
MARIO: MAth Reasoning with code Interpreter Output -- A Reproducible Pipeline
https://github.com/MCLYang/RhythmGAN_pytorch
https://github.com/MINGG2333/bert_ms
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/MLH-Fellowship/Social-BERTerfly
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.