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- W3120352510 abstract "This paper investigates a new co-attention mechanism in neural transduction models for machine translation tasks. We propose a paradigm, termed Two-Headed Monster (THM), which consists of two symmetric encoder modules and one decoder module connected with co-attention. As a specific and concrete implementation of THM, Crossed Co-Attention Networks (CCNs) are designed based on the Transformer model. We test CCNs on WMT 2014 EN-DE and WMT 2016 EN-FI translation tasks and show both advantages and disadvantages of the proposed method. Our model outperforms the strong Transformer baseline by 0.51 (big) and 0.74 (base) BLEU points on EN-DE and by 0.17 (big) and 0.47 (base) BLEU points on EN-FI but the epoch time increases by circa 75%." @default.
- W3120352510 created "2021-01-18" @default.
- W3120352510 creator A5002228588 @default.
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- W3120352510 date "2020-12-01" @default.
- W3120352510 modified "2023-09-23" @default.
- W3120352510 title "Two-Headed Monster and Crossed Co-Attention Networks." @default.
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