Unsupervised Multimodal Neural Machine Translation with Pseudo Visual Pivoting (2020.acl-main)
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| Challenge: | Unsupervised machine translation (MT) has recently achieved impressive results with monolingual corpora. |
| Approach: | They propose to utilize visual content for disambiguation and promoting latent space alignment in unsupervised machine translation by using multimodal back-translation and pseudo visual pivoting. |
| Outcome: | The proposed model improves over state-of-the-art methods and generalizes well when images are not available at the testing time. |
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