This, IMO, is the actual biggest problem with LLMs training on whatever the biggest text corpus us that's available: they don't account for the fact that not all text is equally worthy of next-token-predicting. This problem is completely solvable, almost trivially so, but I haven't seen anyone publicly describe a (scaled, in production) solution yet.