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Source Identification Is Not Fitness Testing: Measuring the Limits of Synthetic-Data Attribution

Armstrong, Joss
arXiv (All) · Papers
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Repeated training on model-generated data can degrade later models. One possible response is to use provenance when deciding which generated examples to reuse. We test both how reliably that provenance can be recovered and whether it helps identify better training data. Using financial-risk text, we
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