FINE-GRAINED AND POLARITY-BASED BENCHMARKS

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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.

Papers with fine-grained and polarity-based benchmarks