https://github.com/BinWang28/BERT_Sentence_Embedding
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Papers with Code 아카이브
Natural Language Understanding
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 2
- 평가표
- 6
- 보존된 평가 기록
- 42
Natural Language Understanding is an important field of Natural Language Processing which contains various tasks such as text classification, natural language inference and story comprehension. Applications enabled by natural language understanding range from question answering to automated reasoning.
Source: Find a Reasonable Ending for Stories: Does Logic Relation Help the Story Cloze Test?
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/BinWang28/SBERT-WK-Sentence-Embedding
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/Bingo-W/Personalisation-in-LLM
https://github.com/BirgerMoell/bertcastle
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/BrianPulfer/PapersReimplementations
https://github.com/BroCoLySTyLe/SQLovaReview
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/BunsenFeng/M-AbstainQA
The Belebele Benchmark: a Parallel Reading Comprehension Dataset in 122 Language Variants
https://github.com/CERT-Lab/fed-sb
FedEx-LoRA: Exact Aggregation for Federated and Efficient Fine-Tuning of Foundation Models
https://github.com/CGCL-codes/naturalcc
https://github.com/CLUEbenchmark/LGEB
https://github.com/CVxTz/music_genre_classification
https://github.com/Caesarzhang/bert-zh
https://github.com/Chang-Chia-Chi/SaintPlus-Knowledge-Tracing-Pytorch
https://github.com/Charliesgithub20221030/BERT
https://github.com/Chenny0808/ape210k
Ape210K: A Large-Scale and Template-Rich Dataset of Math Word Problems
https://github.com/Chinnu1103/Machine-Translation-using-Transformers
https://github.com/Chonwai/Learning_BERT
https://github.com/ChristophReich1996/HyperMixer
HyperMixer: An MLP-based Low Cost Alternative to Transformers
https://github.com/Coda-s/BJTU_NLP_Practice
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/Colanim/BERT_STS-B
https://github.com/Conchylicultor/DeepQA
https://github.com/CongBao/ChatBot
https://github.com/CyberZHG/keras-bert
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/DJJune/Transformer
https://github.com/DSInCenter/Persian-Atis
A Persian Benchmark for Joint Intent Detection and Slot Filling
https://github.com/DanieleVeri/deep_comedy
https://github.com/DataCanvasIO/Hypernets
https://github.com/DataScienceNigeria/Supervised-NLP-from-Facebook-AI-Team
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/Dave870907/Transformer
https://github.com/DeligientSloth/QQsim
https://github.com/DeligientSloth/bert-tensorflow
https://github.com/DenseAI/awesome-biomedical-machine-learning
https://github.com/DenseAI/awesome-medical-machine-learning
https://github.com/DeokO/bert-excercise-ongoing
https://github.com/DevSinghSachan/multilingual_nmt
https://github.com/DimasDMM/nlp-completer
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.