Finally, others have used reinforcement learning to improve informativeness and reduce contradictory information in abstractive summaries, e.g., Pasunuru and Bansal (2018) used a textual entailment-based reward and Arumae and Liu (2019), a question-answering based reward.
these approaches don't evaluate if these rewards improve faithfulness of summaries.