[psb217]

In a sense, poorly reproducing rare content is a form of compression artifact. Ie, since this content occurs rarely in the training set, it will have less impact on the gradients and thus less impact on the final form of the model. Roughly speaking, the model is allocating fewer bits to this content, by storing less information about this content in its parameters, compared to content which it sees more often during training. I think this isn't too different from certain aspects of images, videos, music, etc., being distorted in different ways based on how a particular codec allocates its available bits.