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/frankaging/Causal-Distill
DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter
https://github.com/frankcgq105/BERTCHEN
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/franknb/Text-Summarization
DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter
https://github.com/freedomintelligence/sdak
CBLUE: A Chinese Biomedical Language Understanding Evaluation Benchmark
https://github.com/fshdnc/enfi-XLM
https://github.com/fuhuamosi/MatchLstm
https://github.com/fulstock/mrc_nested_ner_ru
Adaptation of Deep Bidirectional Multilingual Transformers for Russian Language
https://github.com/fwbrandao/Abstractive_Summarisation
https://github.com/fywalter/label-bias
https://github.com/g-eklund/bert_tutorial
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/galkesten/Domestic-Violence-Classifier
Supervised Learning of Universal Sentence Representations from Natural Language Inference Data
https://github.com/galsang/ABCNN
ABCNN: Attention-Based Convolutional Neural Network for Modeling Sentence Pairs
https://github.com/galsang/BIMPM-pytorch
Bilateral Multi-Perspective Matching for Natural Language Sentences
https://github.com/galsang/galsang
Dynamic Compositionality in Recursive Neural Networks with Structure-aware Tag Representations
https://github.com/ganeshjawahar/interpret_bert
SentEval: An Evaluation Toolkit for Universal Sentence Representations
https://github.com/gaochang-bjtu/1-bit-fqt
A Statistical Framework for Low-bitwidth Training of Deep Neural Networks
https://github.com/gaohuan2015/NLPTool
Multi-Task Deep Neural Networks for Natural Language Understanding
https://github.com/gaotianyu1350/SentEval
SentEval: An Evaluation Toolkit for Universal Sentence Representations
https://github.com/gatech-eic/s3-router
data2vec: A General Framework for Self-supervised Learning in Speech, Vision and Language
https://github.com/gbcolborne/lang_id
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/gchhablani/multilingual-vqa
https://github.com/gcunhase/embracebert
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/geondopark/ckd
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/geraltofrivia/match-lstm-ptr-network
https://github.com/getalp/disambiguate
FlauBERT: Unsupervised Language Model Pre-training for French
https://github.com/ggerganov/llama.cpp
https://github.com/gggggeun/DeepLearning_Architecture
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/ggml-org/llama.cpp
https://github.com/glassroom/heinsen_routing
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/gmpoli/electramed
https://github.com/gmum/dl-mo-2021
https://github.com/goel96vibhor/AdvSentEval
SentEval: An Evaluation Toolkit for Universal Sentence Representations
https://github.com/goldenbili/Bert_Test2
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/goldenbili/Bert_Test3
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/goldenbili/bert_lamb_pretrain
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.