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/devJWSong/bert-crf-entity-recognition-pytorch
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/dhiraa/tener
https://github.com/dhlee347/pytorchic-bert
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/diabhaque/Sixth-Sense
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/dispink/xpt
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/dl-nlp/dl-nlp.github.io
https://github.com/dmis-lab/liquid
Quoref: A Reading Comprehension Dataset with Questions Requiring Coreferential Reasoning
https://github.com/dmlc/gluon-nlp
https://github.com/dqqcasia/st
https://github.com/dreamgonfly/BERT-pytorch
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/dreamgonfly/Transformer-pytorch
https://github.com/dreamnotover/english_chinese_machine_translation_baseline
https://github.com/drumpt/Transformer
https://github.com/duyunshu/bert-sentiment-analysis
https://github.com/dyq0811/EEG-Transformer-seq2seq
https://github.com/dzqjorking/transpose
https://github.com/eagle705/bert
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/eaishwa/quora-ques-pair-similarity
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/eleanorye00/Gamifier
https://github.com/elenalenaelena/machine-learning-viz
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/emanuele-progr/PSSP
https://github.com/enhuiz/torchnmt
https://github.com/enhuiz/transformer-pytorch
https://github.com/enod/arxiv-nlp-notes
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/epcpu/deep-nlp-links
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/epfml/collaborative-attention
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/ericperfect/Bert_Position_BiLSTM_Attention_CRF_LSTMDecoder
https://github.com/eternityyw/tram-benchmark
https://github.com/ethancaballero/neural-engineers-first-attempt
https://github.com/ethanjperez/true_few_shot
https://github.com/eunseo1092/Graduation_project
https://github.com/evtaktasheva/dependency_extraction
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/ewdowiak/Sicilian_Translator
https://github.com/exa-labs/exa-mcp-server
https://github.com/extensive-nlp/TSAI-DeepNLP-END2.0
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.