Romain Paulus

A Deep Reinforced Model for Abstractive Summarization

2017 · arXiv (Cornell University)

Attentional, RNN-based encoder-decoder models for abstractive summarization have achieved good performance on short input and output sequences. For longer documents and summaries however these models often include repetitive and incoherent phrases. We introduce a neural …

Ask Me Anything: Dynamic Memory Networks for Natural Language Processing

2015 · arXiv (Cornell University)

Most tasks in natural language processing can be cast into question answering (QA) problems over language input. We introduce the dynamic memory network (DMN), a neural network architecture which processes input sequences and questions, forms …