SMTS Multi sim

Reported on 6 benchmarks across 2 tasks · 1 paper · 4 SOTA

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

Natural Language Processing6 results

Cross-LingualonCoNLL German
F1· 2020-04-26
75.33
SOTA
Single-/Multi-Source Cross-Lingual NER via Teacher-Student Learning on Unlabeled Data in Target Language arXiv:2004.12440
Cross-LingualonCoNLL Spanish
F1· 2020-04-26
78
best: 79.5 (XLM-R large)
SOTA
Single-/Multi-Source Cross-Lingual NER via Teacher-Student Learning on Unlabeled Data in Target Language arXiv:2004.12440
Cross-Lingual TransferonCoNLL German
F1· 2020-04-26
75.33
SOTA
Single-/Multi-Source Cross-Lingual NER via Teacher-Student Learning on Unlabeled Data in Target Language arXiv:2004.12440
Cross-Lingual TransferonCoNLL Spanish
F1· 2020-04-26
78
best: 79.5 (XLM-R large)
SOTA
Single-/Multi-Source Cross-Lingual NER via Teacher-Student Learning on Unlabeled Data in Target Language arXiv:2004.12440
Cross-LingualonCoNLL Dutch
F1· 2020-04-26
81.33
best: 83.35 (Zero shot mBERT 3)
Single-/Multi-Source Cross-Lingual NER via Teacher-Student Learning on Unlabeled Data in Target Language arXiv:2004.12440
Cross-Lingual TransferonCoNLL Dutch
F1· 2020-04-26
81.33
best: 83.35 (Zero shot mBERT 3)
Single-/Multi-Source Cross-Lingual NER via Teacher-Student Learning on Unlabeled Data in Target Language arXiv:2004.12440