Why Self-Attention? A Targeted Evaluation of Neural Machine Translation Architectures

EMNLP 2018 Gongbo TangMathias MüllerAnnette RiosRico Sennrich

Recently, non-recurrent architectures (convolutional, self-attentional) have outperformed RNNs in neural machine translation. CNNs and self-attentional networks can connect distant words via shorter network paths than RNNs, and it has been speculated that this improves their ability to model long-range dependencies... (read more)

PDF Abstract EMNLP 2018 PDF EMNLP 2018 Abstract

Results from the Paper


  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.

Methods used in the Paper


METHOD TYPE
🤖 No Methods Found Help the community by adding them if they're not listed; e.g. Deep Residual Learning for Image Recognition uses ResNet