TL;DR本文提出了一种新的encoder-decoder模型来解决NLP中的sequence to sequence prediction任务，新模型考虑了整个输入序列并引入复制机制来有效处理小样本集和OOV问题。在Gigaword数据集和DUC竞赛中，该模型的性能超过了现有模型。
Abstract
encoder-decoder models have been widely used to solve sequence to sequence prediction tasks. However current approaches suffer from two shortcomings. First, the encoders compute a representation of each word taki