Though TF enables efficient training, it results in "exposure bias" because agents must follow learned rather than gold trajectories at test time.
(ii) Student-forcing (SF), where an action a S is drawn from the current learned policy, allows the agent to learn from its own actions (aligning training and evaluation), however, it is inefficient, as the agent explores randomly when confused or in the early stages of training.