Newer text-to-image models produce less diverse synthetic data, causing classifiers trained solely on them to show declining accuracy on real test sets.
Just say the name: Online continual learning with category names only via data generation.arXiv, 2024
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When Pretty Isn't Useful: Investigating Why Modern Text-to-Image Models Fail as Reliable Training Data Generators
Newer text-to-image models produce less diverse synthetic data, causing classifiers trained solely on them to show declining accuracy on real test sets.