Papers with target language generation
Improving Multilingual Neural Machine Translation by Utilizing Semantic and Linguistic Features (2024.findings-acl)
Copied to clipboard
| Challenge: | Existing models do not differentiate between semantic and linguistic features, resulting in the entanglement of knowledge and linguistics within the model. |
| Approach: | They propose to exploit both semantic and linguistic features to enhance multilingual translation by disentangling encoder representations and integrating low-level linguistic encoders. |
| Outcome: | The proposed model improves zero-shot translation while maintaining performance in supervised translation on multilingual datasets. |