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/giagia96/DeepComedy
https://github.com/glassroom/heinsen_routing
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/glouppe/info8010-deep-learning
https://github.com/gmum/dl-mo-2021
https://github.com/going-doer/paper2code
https://github.com/goldenbili/Bert_Test2
https://github.com/goldenbili/Bert_Test3
https://github.com/goldenbili/bert_lamb_pretrain
https://github.com/goodluck4s/bert-
https://github.com/google-deepmind/xquad
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/google-research-datasets/gap-coreference
Mind the GAP: A Balanced Corpus of Gendered Ambiguous Pronouns
https://github.com/google-research/bigbird
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/google-research/t5x
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
https://github.com/google-research/t5x_retrieval
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
https://github.com/google-research/text-to-text-transfer-transformer
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
https://github.com/google/flax/tree/master/examples/wmt
https://github.com/google/paxml
https://github.com/google/seqio
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/gooofy/zbrain
https://github.com/gooppe/transformer-summarization
https://github.com/gordicaleksa/pytorch-original-transformer
https://github.com/gouwenrui/cpe-pro-main
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/grantslatton/llama.cpp
https://github.com/graykode/gpt-2-Pytorch
https://github.com/graykode/nlp-tutorial
https://github.com/griff4692/LMC
https://github.com/guillaume-chevalier/Linear-Attention-Recurrent-Neural-Network
https://github.com/gulucaptain/dynamictrl
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
https://github.com/guoyaohua/BERT-Chinese-Annotation
https://github.com/guoyaohua/BERT-Classifier
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/guzhang480/Google_BERT
https://github.com/h4ste/oscar
https://github.com/habibullah-araphat/BERT-GPU
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/habibullah-araphat/BERT-NER-TPU
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/haidershaour/bert
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.