Before revision:  Systematic experiments  show that we successfully address the hierarchy bypassing problem and substantially improve the performance of sequence-to-sequence learning with deep representations on diverse tasks  .
After revision:  Systematic experiments show that we successfully address the hierarchy bypassing problem and substantially improve the performance of sequence-to-sequence learning with deep representations on diverse tasks , i.e., machine translation, abstractive summarization and image captioning. In particular, our approach surpasses the previous state-of-the-art models on three benchmark machine translation datasets .