Papers with Code 아카이브
Coreference Resolution
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
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- 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/PaddlePaddle/PaddleSpeech
https://github.com/PaddlePaddle/models
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/Pezhin/best_yelp_review_project_ever
https://github.com/PrashantRanjan09/Elmo-Tutorial
https://github.com/PrashantRanjan09/WordEmbeddings-Elmo-Fasttext-Word2Vec
https://github.com/PrideLee/sentiment-analysis
https://github.com/Priyanshiguptaaa/CoLA_Sentence_Classification_BERT
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/ProsusAI/finBERT
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/Qordobacode/fitbert
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/R1j1t/contextualSpellCheck
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/RUCAIBox/LLMBox
https://github.com/Raman-Raje/Machine-Reading-Comprehension-Neural-Question-Answer-
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/Rami97rgb/French-to-English-Translator
https://github.com/Remiphilius/PoemesProfonds
https://github.com/RenXiangyuan/tf_bert
https://github.com/RonRaifer/BERT-Ghazali
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/Rudedaisy/attention-is-all-you-need-pytorch
https://github.com/RundongChou/elmo-chinese-oversimplified
https://github.com/RxstydnR/Stock_BERT
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/SAP-samples/acl2019-commonsense
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/SAP-samples/acl2019-commonsense-reasoning
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/SAP-samples/acl2020-commonsense
https://github.com/SCismycat/bert_code_view
https://github.com/SYangDong/bert-with-frozen-code
https://github.com/Samyu0304/thought-propagation
https://github.com/Sanyuan-Chen/RecAdam
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/Satan012/BERT
https://github.com/SatyamSoni23/Smart-Question-Answering-System-on-Document
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/SeoroMin/transformer_pytorch
https://github.com/SeoroMin/transformer_pytorch_ver2
https://github.com/Sharif-SLPL/t5-fa
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
https://github.com/Shasvat-Desai/Shasvat-Desai
https://github.com/Shinya-Kouda/kgc
https://github.com/ShivamRajSharma/Transformer-Architectures-From-Scratch
https://github.com/ShuvenduBikash/transformer_spelling_corrector
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.