That's effectively what you get in either case. With MLM, on the first learning iteration you might only mask exactly one token per sequence. This is equivalent to starting learning at a later state. The direction of the curriculum flows toward more and more of these being masked over time, which is equivalent to starting from earlier and earlier states. Eventually, you mask 100% of the sequence and you are starting from zero.