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XLM-E: Cross-lingual Language Model Pre-training via ELECTRA (2106.16138v2)

Published 30 Jun 2021 in cs.CL

Abstract: In this paper, we introduce ELECTRA-style tasks to cross-lingual LLM pre-training. Specifically, we present two pre-training tasks, namely multilingual replaced token detection, and translation replaced token detection. Besides, we pretrain the model, named as XLM-E, on both multilingual and parallel corpora. Our model outperforms the baseline models on various cross-lingual understanding tasks with much less computation cost. Moreover, analysis shows that XLM-E tends to obtain better cross-lingual transferability.

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Authors (11)
  1. Zewen Chi (29 papers)
  2. Shaohan Huang (79 papers)
  3. Li Dong (154 papers)
  4. Shuming Ma (83 papers)
  5. Bo Zheng (205 papers)
  6. Saksham Singhal (14 papers)
  7. Payal Bajaj (13 papers)
  8. Xia Song (38 papers)
  9. Xian-Ling Mao (76 papers)
  10. Heyan Huang (107 papers)
  11. Furu Wei (291 papers)
Citations (116)