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Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
Complex, compositional reading comprehension datasets require performing latent sequential decisions that are learned via supervision from the final answer. A large combinatorial space of possible decision paths that result in the same answer, compounded by the lack of intermediate supervision to help choose the right path, makes the learning particularly hard for this task. In this work, we study the benefits of collecting intermediate reasoning supervision along with the answer during datadoi:10.18653/v1/2020.acl-main.497 fatcat:5hnb2cz6ubfvlbh5jwzwbzngea