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Status: Unchecked ×Keyword: cross-lingual classification ×Clear all

3 claims from 1 paper

1. Computer Science › Topic Modeling

   Cross-lingual Language Model Pretraining

   Lample and Conneau · arXiv (Cornell University) · 2019

   The paper extends generative pretraining to many languages with two cross-lingual language model methods, and reports state-of-the-art results on cross-lingual classification and on unsupervised and supervised machine translation.

   Unchecked3 claims
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   1. UncheckedOn the XNLI benchmark, the authors' cross-lingual pretraining approach is reported to beat the previous best accuracy by 4.9 percentage points.“On XNLI, our approach pushes the state of the art by an absolute gain of 4.9% accuracy.”
   2. UncheckedA cross-lingual pretrained model reaches 34.3 BLEU on unsupervised German-English translation (WMT'16), over 9 BLEU above the previous best.“On unsupervised machine translation, we obtain 34.3 BLEU on WMT'16 German-English, improving the previous state of the art by more than 9 BLEU.”
   3. UncheckedThe authors report 38.5 BLEU on WMT'16 Romanian-English supervised translation, over 4 BLEU above the previous best approach.“On supervised machine translation, we obtain a new state of the art of 38.5 BLEU on WMT'16 Romanian-English, outperforming the previous best approach by more than 4 BLEU.”