HyperAI
HyperAI
الرئيسية
الأخبار
الأوراق البحثية
الدروس
مجموعات البيانات
الموسوعة
SOTA
نماذج LLM
لوحة الأداء GPU
الفعاليات
البحث
حول
العربية
HyperAI
HyperAI
Toggle sidebar
البحث في الموقع...
⌘
K
البحث في الموقع...
⌘
K
الرئيسية
SOTA
التعرف على الكيانات المسماة
Named Entity Recognition On Conll
Named Entity Recognition On Conll
المقاييس
F1
النتائج
نتائج أداء النماذج المختلفة على هذا المعيار القياسي
Columns
اسم النموذج
F1
Paper Title
Repository
BiLSTM-CRF+ELMo
93.42
Deep contextualized word representations
-
LUKE + SubRegWeigh (K-means)
95.27
SubRegWeigh: Effective and Efficient Annotation Weighing with Subword Regularization
-
Pooled Flair
94.13
CrossWeigh: Training Named Entity Tagger from Imperfect Annotations
-
Noise-robust Co-regularization + LUKE
95.60
Learning from Noisy Labels for Entity-Centric Information Extraction
-
LSTM-CRF
91.47
Neural Architectures for Named Entity Recognition
-
Noise-robust Co-regularization + BERT-large
94.04
Learning from Noisy Labels for Entity-Centric Information Extraction
-
RoBERTa + SubRegWeigh (K-means)
95.45
SubRegWeigh: Effective and Efficient Annotation Weighing with Subword Regularization
-
CrossWeigh + Pooled Flair
94.28
CrossWeigh: Training Named Entity Tagger from Imperfect Annotations
-
CL-KL
94.81
Improving Named Entity Recognition by External Context Retrieving and Cooperative Learning
-
LUKE(Large)
95.89
LUKE: Deep Contextualized Entity Representations with Entity-aware Self-attention
-
BiLSTM-CNN-CRF
91.87
End-to-end Sequence Labeling via Bi-directional LSTM-CNNs-CRF
-
0 of 11 row(s) selected.
Previous
Next