IMPROVING MODEL WITH SYNTHETIC DATA

Summary from the TLDR AI newsletter

Researchers have developed a Synthetic-Domain Alignment (SDA) framework to enhance test-time adaptation (TTA) methods. SDA effectively aligns source and synthetic domains by fine-tuning pretrained models with synthetic data generated through a conditional diffusion model.