Does any use of synthetic training data cause collapse?
No. Outcomes depend on the training process, retention of real data, sampling, coverage and verification. Replacement-only recursive experiments do not establish that all synthetic data is harmful.
Answered in
Synthetic Data and Model Collapse: Why Verification Helps but Is Not EnoughRecursive synthetic training can lose distributional diversity. Retaining real data, evaluating coverage and using suitable verifiers can reduce the risk.
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