While scheduled sampling  is an effective way to rectify exposure bias, it cannot differentiate between cascading errors, which can lead to a sequence of bad decisions, and local errors, which have more benign effects.
scheduled sampling focuses on learning optimal behavior in the current step given the fixed decoding decision of the previous step.