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arXiv · 2009.09672

Alleviating the Inequality of Attention Heads for Neural Machine Translation

Zewei Sun·Shujian Huang·Xin-Yu Dai·Jiajun Chen
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Abstract

Recent studies show that the attention heads in Transformer are not equal. We relate this phenomenon to the imbalance training of multi-head attention and the model dependence on specific heads. To tackle this problem, we propose a simple masking method: HeadMask, in two specific ways. Experiments show that translation improvements are achieved on multiple language pairs. Subsequent empirical analyses also support our assumption and confirm the effectiveness of the method.

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Zewei Sun, Shujian Huang, Xin-Yu Dai, Jiajun Chen. 2020-09-21. Alleviating the Inequality of Attention Heads for Neural Machine Translation. https://arxiv.org/abs/2009.09672

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