Cross-BiLSTM-CNN

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)onWNUT 2017
Precision· 2019-08-29
58.28
SOTA
Why Attention? Analyze BiLSTM Deficiency and Its Remedies in the Case of NER arXiv:1908.11046
Named Entity Recognition (NER)onWNUT 2017
Recall· 2019-08-29
33.92
SOTA
Why Attention? Analyze BiLSTM Deficiency and Its Remedies in the Case of NER arXiv:1908.11046
Named Entity Recognition (NER)onWNUT 2017
F1· 2019-08-29
42.85
best: 60.45 (CL-KL)
Why Attention? Analyze BiLSTM Deficiency and Its Remedies in the Case of NER arXiv:1908.11046