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홈뉴스최신 연구 논문튜토리얼데이터셋백과사전SOTALLM 모델GPU 랭킹컨퍼런스
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Chinese Named Entity Recognition On Weibo Ner

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F1

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이 벤치마크에서 각 모델의 성능 결과

모델 이름
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Paper TitleRepository
Lattice58.79Chinese NER Using Lattice LSTM
TENER58.17TENER: Adapting Transformer Encoder for Named Entity Recognition-
SLK-NER64SLK-NER: Exploiting Second-order Lexicon Knowledge for Chinese NER
FLAT+BERT68.55FLAT: Chinese NER Using Flat-Lattice Transformer
FGN71.25FGN: Fusion Glyph Network for Chinese Named Entity Recognition
Glyce + BERT67.6Glyce: Glyph-vectors for Chinese Character Representations
Locate and Label69.16Locate and Label: A Two-stage Identifier for Nested Named Entity Recognition-
AESINER69.78Improving Named Entity Recognition with Attentive Ensemble of Syntactic Information
Collaborative Graph Network63.09Leverage Lexical Knowledge for Chinese Named Entity Recognition via Collaborative Graph Network
Baseline + BS72.66Boundary Smoothing for Named Entity Recognition
BERT-BiLSTM-context70.98Supplementary Features of BiLSTM for Enhanced Sequence Labeling
BiLSTM+CRF+adversarial+self-attention53.08Adversarial Transfer Learning for Chinese Named Entity Recognition with Self-Attention Mechanism
SA-NER69.8Named Entity Recognition for Social Media Texts with Semantic Augmentation
FLAT60.32FLAT: Chinese NER Using Flat-Lattice Transformer
BERT-CRF (Replicated in AdaSeq)72.77Improving Named Entity Recognition by External Context Retrieving and Cooperative Learning
CAN-NER Model-CAN-NER: Convolutional Attention Network for Chinese Named Entity Recognition
LSTM + Lexicon augment61.24Simplify the Usage of Lexicon in Chinese NER
NFLAT61.94NFLAT: Non-Flat-Lattice Transformer for Chinese Named Entity Recognition
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