Semi-Autoregressive Training Improves Mask-Predict Decoding

• URL: http://arxiv.org/abs/2001.08785v1
• Date: Thu, 23 Jan 2020 19:56:35 GMT
• Title: Semi-Autoregressive Training Improves Mask-Predict Decoding
• Authors: Marjan Ghazvininejad, Omer Levy, Luke Zettlemoyer
• Abstract summary: We introduce a new training method for conditional masked language models, SMART, which mimics the semi-autoregressive behavior of mask-predict. Models trained with SMART produce higher-quality translations when using mask-predict decoding, effectively closing the remaining performance gap with fully autoregressive models.
• Score: 119.8412758943192
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: The recently proposed mask-predict decoding algorithm has narrowed the performance gap between semi-autoregressive machine translation models and the traditional left-to-right approach. We introduce a new training method for conditional masked language models, SMART, which mimics the semi-autoregressive behavior of mask-predict, producing training examples that contain model predictions as part of their inputs. Models trained with SMART produce higher-quality translations when using mask-predict decoding, effectively closing the remaining performance gap with fully autoregressive models.

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