An Empirical Study of Adequate Vision Span for Attention-Based Neural Machine Translation

WS 2017 Raphael ShuHideki Nakayama

Recently, the attention mechanism plays a key role to achieve high performance for Neural Machine Translation models. However, as it computes a score function for the encoder states in all positions at each decoding step, the attention model greatly increases the computational complexity... (read more)

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