Papers by Paweł Maka
Sequence Shortening for Context-Aware Machine Translation (2024.findings-eacl)
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| Challenge: | Context-aware Machine Translation aims to improve translations of sentences by incorporating surrounding sentences as context. |
| Approach: | They propose to use latent representation of source sentence as context in a multi-encoder architecture to achieve higher accuracy on contrastive datasets. |
| Outcome: | The proposed architectures achieve comparable BLEU and COMET scores on contrastive datasets and comparable accuracies on the single- and multi-encoder approaches. |