MacNet: Transferring Knowledge from Machine Comprehension to Sequence-to-Sequence Models

NeurIPS 2018 Boyuan PanYazheng YangHao LiZhou ZhaoYueting ZhuangDeng CaiXiaofei He

Machine Comprehension (MC) is one of the core problems in natural language processing, requiring both understanding of the natural language and knowledge about the world. Rapid progress has been made since the release of several benchmark datasets, and recently the state-of-the-art models even surpass human performance on the well-known SQuAD evaluation... (read more)

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