Study: Generated images often can’t be traced to specific training examples as datasets grow
A new study introduces a method for surgically removing individual training examples from a model and reports that, as datasets scale up, the link between what a model learns and what it later generates weakens — generated images often can’t be reliably traced back to particular training images. The finding suggests limits to tracing, attributing, or excising specific content from large generative models.