2022
ACL
ACL 2022
XLM-E: Cross-lingual Language Model Pre-training via ELECTRA
Abstract
AbstractIn this paper, we introduce ELECTRA-style tasks to cross-lingual language model 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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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Security & Privacy, Speech & Audio
Authors
Zewen Chi
,
Shaohan Huang
,
Li Dong
,
Shuming Ma
,
Bo Zheng
,
Saksham Singhal
,
Payal Bajaj
,
XIA SONG
,
Xian-Ling Mao
,
Heyan Huang
,
Furu Wei