Papers with Code 아카이브
Natural Language Inference
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 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/kyegomez/GPT3
https://github.com/kyubyong/bert_ner
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/kyzhouhzau/BERT-NER
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/labmlai/annotated_deep_learning_paper_implementations
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/lambert-x/prolab
https://github.com/laohur/LearnToCompareText
https://github.com/laohur/RelationNet
https://github.com/lashoun/hanna-benchmark-asg
https://github.com/lattice-ai/GPT
https://github.com/lcs2-iiitd/emotion-flip-reasoning
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/leaderj1001/Bag-of-MLP
https://github.com/leejieun51/transformer
https://github.com/lehoanganh298/BERT-Question-Answering
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/lemonhu/ner-bert-pytorch
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/lennonzurich/lalala
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/leondgarse/keras_cv_attention_models/tree/main/keras_cv_attention_models/mlp_family
https://github.com/lesterpjy/numeric-t5
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
https://github.com/liangyuxin42/SimCSE-reproduce
https://github.com/libowen2121/SNLI-decomposable-attention
A Decomposable Attention Model for Natural Language Inference
https://github.com/lichengunc/pretrain-vl-data
https://github.com/lindermanlab/S5
Hungry Hungry Hippos: Towards Language Modeling with State Space Models
https://github.com/linghao-jin/canmt-challenges
MABEL: Attenuating Gender Bias using Textual Entailment Data
https://github.com/linlei1214/SITS-BERT
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/liqichen6688/duo-attention
https://github.com/listenviolet/XLNet
XLNet: Generalized Autoregressive Pretraining for Language Understanding
https://github.com/liuqiangict/lamb_optimizer
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/liuruiyang98/Jittor-MLP
https://github.com/lkfo415579/MT-Readling-List
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/llx666/git_demo
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/lonePatient/BERT-SDA
Improving BERT Fine-Tuning via Self-Ensemble and Self-Distillation
https://github.com/lonePatient/BERT-chinese-text-classification-pytorch
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/lonePatient/Bert-Multi-Label-Text-Classification
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/lonePatient/ERNIE-text-classification-pytorch
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/lonePatient/albert_pytorch
ALBERT: A Lite BERT for Self-supervised Learning of Language Representations
https://github.com/lonePatient/bert-sentence-similarity-pytorch
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.