Papers with Code 아카이브
Coreference Resolution
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 2
- 평가표
- 16
- 보존된 평가 기록
- 154
Coreference resolution is the task of clustering mentions in text that refer to the same underlying real world entities.
Example:
+-----------+
| |
I voted for Obama because he was most aligned with my values", she said.
| | |
+-------------------------------------------------+------------+
"I", "my", and "she" belong to the same cluster and "Obama" and "he" belong to the same cluster.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/BroCoLySTyLe/SQLovaReview
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/CGCL-codes/naturalcc
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/ChernovAndrey/chronos-forecasting-wasserstein
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
https://github.com/Chinnu1103/Machine-Translation-using-Transformers
https://github.com/Chonwai/Learning_BERT
https://github.com/ClaudiaRaffaelli/Protein-subcellular-localization
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/CyberZHG/keras-bert
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/DJJune/Transformer
https://github.com/DanieleVeri/deep_comedy
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/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
https://github.com/DimasDMM/transformers
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/Doffery/BERT-Sentiment-Analysis-Amazon-Review
https://github.com/Domminique/Deploy-BERT-for-Sentiment-Analysis-with-FastAPI-
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/Dongcf/Pytorch_Bert_Text_Classification
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/DylanCope/Image-Captioning-with-Bimodal-Transformers
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/Eeun-ju/NLP-study
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/EightRice/atn_GPT-3
https://github.com/EleutherAI/gpt-neo
https://github.com/EleutherAI/lm-evaluation-harness
https://github.com/EleutherAI/lm_evaluation_harness
https://github.com/ElizaLo/Question-Answering-based-on-SQuAD
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/EmilioTyl/transformers_from_scratch
https://github.com/Enigmatisms/Set-Transformer
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.