Shiv Shankar


2018

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Surprisingly Easy Hard-Attention for Sequence to Sequence Learning
Shiv Shankar | Siddhant Garg | Sunita Sarawagi
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing

In this paper we show that a simple beam approximation of the joint distribution between attention and output is an easy, accurate, and efficient attention mechanism for sequence to sequence learning. The method combines the advantage of sharp focus in hard attention and the implementation ease of soft attention. On five translation tasks we show effortless and consistent gains in BLEU compared to existing attention mechanisms.