Papers with NAG model

2 papers
Non-Autoregressive Text Generation with Pre-trained Language Models (2021.eacl-main)

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Challenge: Autoregressive generation models generate tokens in a left-to-right, token-by-token fashion, resulting in lag in inference.
Approach: They propose to use BERT as the backbone of a non-autoregressive generation model for greatly improved performance.
Outcome: The proposed model outperforms existing non-autoregressive models and achieves competitive performance with many strong autoregressive model.
POS-Constrained Parallel Decoding for Non-autoregressive Generation (2021.acl-long)

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Challenge: Existing non-autoregressive generation systems face multimodality problem due to conditionally independent decoding.
Approach: They propose to incorporate linguistic structure into NAG inference instead of teacher AG . they propose a method that provides a specific POS sequence to constrain the NAG model .
Outcome: The proposed method improves NAG models on four text generation tasks to a greater extent compared to knowledge distillation.

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