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Models/BiLSTM (UN)

BiLSTM (UN)

Reported on 8 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 Processing8 results

  • Cross-LingualonMLDoc Zero-Shot English-to-French
    Accuracy· 2018-05-24
    74.52
    best: 96.05 (XLMft UDA)
    SOTA
    A Corpus for Multilingual Document Classification in Eight LanguagesarXiv:1805.09821
  • Cross-LingualonMLDoc Zero-Shot English-to-Russian
    Accuracy· 2018-05-24
    61.42
    best: 89.7 (XLMft UDA)
    SOTA
    A Corpus for Multilingual Document Classification in Eight LanguagesarXiv:1805.09821
  • Cross-Lingual Document ClassificationonMLDoc Zero-Shot English-to-French
    Accuracy· 2018-05-24
    74.52
    best: 96.05 (XLMft UDA)
    SOTA
    A Corpus for Multilingual Document Classification in Eight LanguagesarXiv:1805.09821
  • Cross-Lingual Document ClassificationonMLDoc Zero-Shot English-to-Russian
    Accuracy· 2018-05-24
    61.42
    best: 89.7 (XLMft UDA)
    SOTA
    A Corpus for Multilingual Document Classification in Eight LanguagesarXiv:1805.09821
  • Cross-LingualonMLDoc Zero-Shot English-to-Chinese
    Accuracy· 2018-05-24
    71.97
    best: 93.32 (XLMft UDA)
    A Corpus for Multilingual Document Classification in Eight LanguagesarXiv:1805.09821
  • Cross-LingualonMLDoc Zero-Shot English-to-Spanish
    Accuracy· 2018-05-24
    69.5
    best: 96.8 (XLMft UDA)
    A Corpus for Multilingual Document Classification in Eight LanguagesarXiv:1805.09821
  • Cross-Lingual Document ClassificationonMLDoc Zero-Shot English-to-Chinese
    Accuracy· 2018-05-24
    71.97
    best: 93.32 (XLMft UDA)
    A Corpus for Multilingual Document Classification in Eight LanguagesarXiv:1805.09821
  • Cross-Lingual Document ClassificationonMLDoc Zero-Shot English-to-Spanish
    Accuracy· 2018-05-24
    69.5
    best: 96.8 (XLMft UDA)
    A Corpus for Multilingual Document Classification in Eight LanguagesarXiv:1805.09821