Papers with Code 아카이브
Natural Language Inference
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Natural language inference (NLI) is the task of determining whether a "hypothesis" is true (entailment), false (contradiction), or undetermined (neutral) given a "premise".
Example:
| Premise | Label | Hypothesis |
|---|---|---|
| A man inspects the uniform of a figure in some East Asian country. | contradiction | The man is sleeping. |
| An older and younger man smiling. | neutral | Two men are smiling and laughing at the cats playing on the floor. |
| A soccer game with multiple males playing. | entailment | Some men are playing a sport. |
Approaches used for NLI include earlier symbolic and statistical approaches to more recent deep learning approaches. Benchmark datasets used for NLI include SNLI, MultiNLI, SciTail, among others. You can get hands-on practice on the SNLI task by following this d2l.ai chapter.
Further readings:
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
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
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/KeithGalli/pycon2020
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
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-
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/KhenAharon/Deep-Learning-SNLI-Residual-Stacked-Encoders
Shortcut-Stacked Sentence Encoders for Multi-Domain Inference
https://github.com/Ki6an/fastT5
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
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/KoshiroSato/Flask_NLP_App
mT5: A massively multilingual pre-trained text-to-text transformer
https://github.com/KoshiroSato/Simple_Transformers_mT5_finetuning
mT5: A massively multilingual pre-trained text-to-text transformer
https://github.com/Kosuke-Szk/BERT-NER-ja
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/KushGrandhi/Polaroid
https://github.com/Kyubyong/bert-token-embeddings
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/LaiXinyi823/emotect
ERNIE: Enhanced Representation through Knowledge Integration
https://github.com/LamLauChiu/Tensorflow_Learning
https://github.com/LawrenceDuan/myLASER
Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyond
https://github.com/Lemoners/Attention-Is-All-You-Need
https://github.com/LeoLaugier/conditional-auto-encoder-text-to-text-transfer-transformer
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
https://github.com/LeoWood/bert-horovod
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/Leputa/CIKM-AnalytiCup-2018
ABCNN: Attention-Based Convolutional Neural Network for Modeling Sentence Pairs
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
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/MFajcik/RumourEval2019
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
https://github.com/MOHAMEDELDAKDOUKY/bert_adjusted
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
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/mobilebert
MobileBERT: a Compact Task-Agnostic BERT for Resource-Limited Devices
https://github.com/MS-P3/code5/tree/main/t5
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
https://github.com/MS-P3/code6/tree/main/finetune
https://github.com/MS-P3/code6/tree/main/inference
Neural Natural Language Inference Models Enhanced with External Knowledge
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