LUKE + SubRegWeigh (K-means)

Reported on 3 benchmarks across 1 task · 1 paper · 2 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Natural Language Processing3 results

Named Entity Recognition (NER)onCoNLL-2020
F1· 2024-09-10
95.31
SOTA
SubRegWeigh: Effective and Efficient Annotation Weighing with Subword Regularization arXiv:2409.06216
Named Entity Recognition (NER)onCoNLL++
F1· 2024-09-10
96.12
SOTA
SubRegWeigh: Effective and Efficient Annotation Weighing with Subword Regularization arXiv:2409.06216
Named Entity Recognition (NER)onCoNLL 2003 (English)
F1· 2024-09-10
94.2
best: 94.6 (ACE + document-context)
SubRegWeigh: Effective and Efficient Annotation Weighing with Subword Regularization arXiv:2409.06216