Papers with universal language representation
Language Scaling for Universal Suggested Replies Model (2021.naacl-industry)
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Qianlan Ying, Payal Bajaj, Budhaditya Deb, Yu Yang, Wei Wang, Bojia Lin, Milad Shokouhi, Xia Song, Yang Yang, Daxin Jiang
| Challenge: | We consider scaling automated suggested replies (SR) to multiple languages for a commercial email application. |
| Approach: | They propose a multi-lingual multi-task continual learning framework with auxiliary tasks and language adapters to train universal language representation across regions. |
| Outcome: | The proposed model reduces catastrophic forgetting and improves cross-lingual transfer across languages while reducing training costs. |
Pre-training Universal Language Representation (2021.acl-long)
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| Challenge: | Despite the cutting-edge representation learning, most language models focus on specific levels of linguistic units. |
| Approach: | They propose a training objective MiSAD that utilizes meaningful n-grams extracted from large unlabeled corpus by an algorithm for pre-trained language models. |
| Outcome: | The proposed model achieves highest accuracy on analogy tasks in different language levels and significantly improves performance on downstream tasks. |