Synthetic Rewriting as a Quality Multiplier: Evidence from Portuguese Continued Pretraining
Synthetic data generation through document rewriting has emerged as a promising technique for improving language model pretraining, yet most studies focus on English and do not systematically control for the quality of the source data being rewritten. We present a controlled study of how synthetic rewriting interacts with source data quality in the context of Portuguese continued pretraining. Starting from ClassiCC-PT, a Portuguese corpus annotated with STEM and Educational quality scores, we construct two 10B-token subsets at different quality levels and rewrite each into four styles using a 7B instruction-tuned model, producing approximately 40B tokens of synthetic data per condition. W...
| Authors | Thales Sales Almeida, Rodrigo Nogueira, Hélio Pedrini |
|---|---|
| Primary category | cs.CL |
| Published | 25 March 2026 |
| Last updated at source | 25 March 2026 |
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