If a generator cannot produce a result that was in the training set due to overly biasing on the most common samples, then yes. If something was in 10% of the inputs and is produced in 1% of the outputs, there is a problem.

I am pretty sure that it's possible to do it in a better way than by mangling prompts, but I will leave that to more capable people. Possible doesn't mean easy.