Papers with Self-supervision
Leveraging Monolingual Data with Self-Supervision for Multilingual Neural Machine Translation (2020.acl-main)
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Aditya Siddhant, Ankur Bapna, Yuan Cao, Orhan Firat, Mia Chen, Sneha Kudugunta, Naveen Arivazhagan, Yonghui Wu
| Challenge: | Existing multilingual NMT approaches do not utilize the abundance of monolingual data, especially in low-resource languages. |
| Approach: | They propose to combine monolingual data with self-supervision to pre-train translation models and fine-tune on small amounts of supervised data. |
| Outcome: | The proposed approach improves translation quality of low-resource languages and zero-shot translation quality. |