Papers with continuous latent variable model

1 papers
Iterative Refinement in the Continuous Space for Non-Autoregressive Neural Machine Translation (2020.emnlp-main)

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Challenge: Existing non-autoregressive inference procedures that refine in token space often require computational overhead.
Approach: They propose an efficient inference procedure that iteratively refines translation purely in the continuous space using a latent variable instead of the latent variables.
Outcome: The proposed procedure is twice as efficient and more effective than the existing EM-like inference procedure.

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