Instead of directly transferring the knowledge to the target domain, this paper proposes to borrow the benefit of multi-task learning, which allows a single model to be capable of handling multiple tasks/domains by feeding the corresponding data.
we utilize question answering for learning the capability of rationalization instead of a rationalizationspecific language model.