XLM-E: Cross-lingual Language Model Pre-training Via ELECTRA | Awesome LLM Papers Contribute to Awesome LLM Papers

XLM-E: Cross-lingual Language Model Pre-training Via ELECTRA

Zewen Chi, Shaohan Huang, Li Dong, Shuming Ma, Bo Zheng, Saksham Singhal, Payal Bajaj, Xia Song, Xian-Ling Mao, Heyan Huang, Furu Wei . Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) 2022 – 61 citations

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ACL Training Techniques

In 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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