1506.03134.Pointer Networks.pdf

https://arxiv.org/pdf/1506.03134.pdf We introduce a new neural architecture to learn the conditional probability of an output sequence with elements that are discrete tokens corresponding to positions in an input sequence. Such problems cannot be trivially addressed by existent approaches such as se