Papers by Xinchen Ma
Unsupervised Text Style Transfer for Controllable Intensity (2026.findings-eacl)
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| Challenge: | Unsupervised Text Style Transfer (UTST) aims to transfer the stylistic properties of a given text without parallel text pairs. |
| Approach: | They propose a SFT-then-PPO paradigm to fine-tune an LLM with parallel data and reward functions for distinguishing stylistic intensity in hierarchical levels. |
| Outcome: | The proposed system can transfer stylistic properties without parallel text pairs even for adjacent levels of intensity. |
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. |