https://github.com/crx934080895/Bert-CRF_New2
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
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/csinva/interpretable-autoprompting
AutoPrompt: Eliciting Knowledge from Language Models with Automatically Generated Prompts
https://github.com/csitfun/logiqa2.0
Transforming Question Answering Datasets Into Natural Language Inference Datasets
https://github.com/cuber2460/bert
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/cuhksz-nlp/SAPar
XLNet: Generalized Autoregressive Pretraining for Language Understanding
https://github.com/cuhksz-nlp/het-mc
ZEN: Pre-training Chinese Text Encoder Enhanced by N-gram Representations
https://github.com/cuhksz-nlp/mcasp
ZEN: Pre-training Chinese Text Encoder Enhanced by N-gram Representations
https://github.com/cui0523/Code6/tree/main/albert
ALBERT: A Lite BERT for Self-supervised Learning of Language Representations
https://github.com/cui0523/Code6/tree/main/ernie
ERNIE: Enhanced Representation through Knowledge Integration
https://github.com/cvolcy/gmlp-tf
https://github.com/cybertronai/megatron-lm
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/cypressd1999/FYP_2021
ALBERT: A Lite BERT for Self-supervised Learning of Language Representations
https://github.com/danlim-wz/analysis_of_social_media_data_about_singapore
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/darr/nerbert
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/darr/nlp_work
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/dashenzi721/hra
https://github.com/dataflowr/self-attentive-sentence-embedding
https://github.com/davidbellamy/labrador
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/davidsvaughn/dts-tf
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/davisliang/fairseq/tree/main/examples/xlmv
XLM-V: Overcoming the Vocabulary Bottleneck in Multilingual Masked Language Models
https://github.com/dawn0815/UniSA
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
https://github.com/dbmdz/historic-ner
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/dc-dc-dc/mlx-rwkv
https://github.com/debnsuma/AmazonSageMaker101
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/debnsuma/Intro-Transformer-BERT
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/deep-spin/entmax
From Softmax to Sparsemax: A Sparse Model of Attention and Multi-Label Classification
https://github.com/deepmind/xquad
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/deepmipt/Slavic-BERT-NER
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/deepmipt/bert/tree/feat/multi_gpu
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/deepset-ai/FARM
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/demegire/Parameterization-of-Hypercomplex-Multiplications
https://github.com/deping-1/2019-false-news-detection-challenge
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/derronxu/sparsebert
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/deterministic-algorithms-lab/Large-XLM
https://github.com/devJWSong/bert-crf-entity-recognition-pytorch
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/devhemza/BERTweet_sentiment_analysis
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.