Diff4TST: Masked Diffusion Language Model for Text Style Transfer (2026.acl-long)
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| Challenge: | Existing methods for text style transfer rely on task-specific training and expensive training stages. |
| Approach: | They propose a diffusion-based language model that formulates text style transfer as an explicit copy-and-edit process. |
| Outcome: | The proposed model improves style accuracy and controllability while maintaining strong content preservation and fluency. |
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