Recurrent Memory Networks for Language Modeling

Understand

Recurrent Neural Networks (RNN) have obtained excellent result in many natural language processing (NLP) tasks.

• However, understanding and interpreting the source of this success remains a challenge.
• In this paper, we propose Recurrent Memory Network (RMN), a novel RNN architecture, that not only amplifies the power of RNN but also facilitates our understanding of its internal functioning and allows us to discover underlying patterns in data.
• We demonstrate the power of RMN on language modeling and sentence completion tasks.