Papers with Code 아카이브
Linguistic Acceptability
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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Linguistic Acceptability is the task of determining whether a sentence is grammatical or ungrammatical.
Image Source: Warstadt et al
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/sileod/tasksource
공식 코드tasksource: A Dataset Harmonization Framework for Streamlined NLP Multi-Task Learning and Evaluation
https://github.com/sjtu-compling/mela
공식 코드https://github.com/thunlp/ERNIE
공식 코드ERNIE: Enhanced Language Representation with Informative Entities
https://github.com/timdettmers/bitsandbytes
공식 코드LLM.int8(): 8-bit Matrix Multiplication for Transformers at Scale
https://github.com/uclanlp/ProbeGrammarRobustness
공식 코드On the Robustness of Language Encoders against Grammatical Errors
https://github.com/upunaprosk/la-tda
공식 코드https://github.com/zihangdai/xlnet
공식 코드XLNet: Generalized Autoregressive Pretraining for Language Understanding
https://github.com/10-zin/Synthesizer
Synthesizer: Rethinking Self-Attention in Transformer Models
https://github.com/10Exahertz/Text-ResNet-on-Sentimental-LIAR-Fake-News
https://github.com/1wy/bert
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/2023-MindSpore-1/ms-code-11
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/2023-MindSpore-1/ms-code-12
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/2023-MindSpore-1/ms-code-150
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/2023-MindSpore-1/ms-code-163
https://github.com/2023-MindSpore-1/ms-code-164
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
https://github.com/2023-MindSpore-1/ms-code-166
TinyBERT: Distilling BERT for Natural Language Understanding
https://github.com/2023-MindSpore-1/ms-code-219/tree/main/albert
ALBERT: A Lite BERT for Self-supervised Learning of Language Representations
https://github.com/2023-MindSpore-1/ms-code-56
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/2023-MindSpore-4/Code12/tree/main/MindFormers/bert
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/2023-MindSpore-4/Code12/tree/main/MindFormers/t5
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
https://github.com/2024-MindSpore-1/Code2/tree/main/model-1/big_bird
https://github.com/2024-MindSpore-1/Code2/tree/main/model-1/data2vec
data2vec: A General Framework for Self-supervised Learning in Speech, Vision and Language
https://github.com/2024-MindSpore-1/Code2/tree/main/model-1/deberta
https://github.com/2024-MindSpore-1/Code2/tree/main/model-1/deberta_v2
https://github.com/2024-MindSpore-1/Code2/tree/main/model-1/distilbert
DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter
https://github.com/2024-MindSpore-1/Code2/tree/main/model-1/fnet
https://github.com/2024-MindSpore-1/Code3/tree/main/scBERT
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/2miatran/Natural-Language-Processing
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/ABaldrati/MT-BERT
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/AGiannoutsos/COVID19-document-retrieval-with-BERT
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/AbhishekD15/Sentiment-Analysis_BERT
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/AdamStein97/Semi-Supervised-BERT-NER
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/AhmedYounes94/Semi-supervised-BERT-NER
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/Alihassan7726/Fine-tuning-BERT-for-semantic-sentence-pairs-classification
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/Alihassan7726/Multi-Class-classification-using-BERT-
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.