Zero-Shot Translation using Diffusion Models

2021-11-02 · Eliya Nachmani, Shaked Dovrat

In this work, we show a novel method for neural machine translation (NMT), using a denoising diffusion probabilistic model (DDPM), adjusted for textual data, following recent advances in the field. We show that it's possible to translate sentences non-autoregressively using a diffusion model conditioned on the source sentence. We also show that our model is able to translate between pairs of languages unseen during training (zero-shot learning).

📄 PDF Abstract BibTeX arXiv:2111.01471

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Tasks

Denoising Machine TranslationNMTSentenceTranslation Zero-Shot Learning

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