Papers by Jiquan Ngiam
Learning a Multi-Domain Curriculum for Neural Machine Translation (2020.acl-main)
Copied to clipboard
| Challenge: | Existing data selection methods do not work well for multiple domains . multiple aspects need to be considered for training a multi-domain model . |
| Approach: | They propose a dynamic data selection method to multi-domain NMT that incorporates instance-level domain-relevance features and a curriculum to gradually focus on multi- domain relevant data batches. |
| Outcome: | The proposed model outperforms no-curriculum training on multiple domains and reaches or outperformed individual performance. |