Abstract
In multilingual pre-training with the objective of MLM (masked language modeling) on multiple monolingual corpora, multilingual models only learn cross-linguality implicitly from isomorphic spaces formed by overlapping different language spaces due to the lack of explicit cross-lingual forward pass. In this work, we present CLPM (Cross-lingual Prototype Masking), a dynamic and token-wise masking scheme, for multilingual pre-training, using a special token [𝒞]x to replace a random token x in the input sentence. [𝒞]x is a cross-lingual prototype for x and then forms an explicit cross-lingual forward pass. We instantiate CLPM for the multilingual pre-training phase of UNMT (unsupervised neural machine translation), and experiments show that CLPM can consistently improve the performance of UNMT models on {De, Ro, Ne } ↔ En. Beyond UNMT or bilingual tasks, we show that CLPM can consistently improve the performance of multilingual models on cross-lingual classification.- Anthology ID:
- 2023.acl-long.49
- Volume:
- Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
- Month:
- July
- Year:
- 2023
- Address:
- Toronto, Canada
- Editors:
- Anna Rogers, Jordan Boyd-Graber, Naoaki Okazaki
- Venue:
- ACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 855–876
- Language:
- URL:
- https://aclanthology.org/2023.acl-long.49
- DOI:
- 10.18653/v1/2023.acl-long.49
- Cite (ACL):
- Xi Ai and Bin Fang. 2023. On-the-fly Cross-lingual Masking for Multilingual Pre-training. In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 855–876, Toronto, Canada. Association for Computational Linguistics.
- Cite (Informal):
- On-the-fly Cross-lingual Masking for Multilingual Pre-training (Ai & Fang, ACL 2023)
- PDF:
- https://preview.aclanthology.org/ingest-acl-2023-videos/2023.acl-long.49.pdf