Papers by Xiaoguang Mao

1 papers
StyleFlow: Disentangle Latent Representations via Normalizing Flow for Unsupervised Text Style Transfer (2024.lrec-main)

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Challenge: Existing methods to separate content from style but some words contain both content and style information.
Approach: They propose a method which uses a reversible encoder to improve content disentanglement.
Outcome: The proposed method outperforms baselines on sentiment transfer and formality transfer tasks.

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