Papers with multiple style-aware language models

1 papers
Multi-Style Transfer with Discriminative Feedback on Disjoint Corpus (2021.naacl-main)

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Challenge: Existing methods for style transfer require joint annotations across all stylistic dimensions, limiting their application to multiple styles.
Approach: They initialize an encoder-decoder setup with transformer-based language model pre-trained on a generic corpus and enhance its re-writing capability to multiple target style dimensions by employing multiple style-aware language models as discriminators.
Outcome: The proposed model can control styles across multiple style dimensions while preserving content of the input text.

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