Papers by Qihan Guo

1 papers
NAST: A Non-Autoregressive Generator with Word Alignment for Unsupervised Text Style Transfer (2021.findings-acl)

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Challenge: Autoregressive text style transfer models often ignore part of the source sentence and generate some irrelevant words with strong styles.
Approach: They propose a non-autoregressive generator for unsupervised text style transfer which explicitly models word alignments to suppress irrelevant words.
Outcome: The proposed generator significantly improves performance and provides explainable word alignments.

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