Philip Yeres


2017

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Sequential Attention: A Context-Aware Alignment Function for Machine Reading
Sebastian Brarda | Philip Yeres | Samuel Bowman
Proceedings of the 2nd Workshop on Representation Learning for NLP

In this paper we propose a neural network model with a novel Sequential Attention layer that extends soft attention by assigning weights to words in an input sequence in a way that takes into account not just how well that word matches a query, but how well surrounding words match. We evaluate this approach on the task of reading comprehension (on the Who did What and CNN datasets) and show that it dramatically improves a strong baseline—the Stanford Reader—and is competitive with the state of the art.