You would not. Many GAN papers do nearest-neighbor lookups, and typically, generated samples are clearly different. Since Arfa's model is high-quality and the interps look fine, I would not expect it to be any different. (It would be hard to check because there are no pretrained classifiers to provide an embedding to do the search in, but one could do reverse-encoding.)
The fact that nearest-neighbor lookups do not find exact overlaps between the training dataset and a large number of random samples has always been one of the arguments I use against the widespread misconception that GANs 'just memorize' data: https://www.gwern.net/Faces#faq
That so many people are convinced that a given datapoint must be an exact copy of a training datapoint - "it looks exactly like a Zootopia character I recognize!" - is really quite a compliment to the GAN...
The fact that nearest-neighbor lookups do not find exact overlaps between the training dataset and a large number of random samples has always been one of the arguments I use against the widespread misconception that GANs 'just memorize' data: https://www.gwern.net/Faces#faq
That so many people are convinced that a given datapoint must be an exact copy of a training datapoint - "it looks exactly like a Zootopia character I recognize!" - is really quite a compliment to the GAN...