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論文解讀:On The Alignment Problem In Multi-Head Attention-Based Neural Machine Translation
時間 2021-01-02
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神經機器翻譯
對齊模型
多頭注意力
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論文解讀:On The Alignment Problem In Multi-Head Attention-Based Neural Machine Translation 機器翻譯是自然語言處理的任務之一。基於transformer和multi-head attention在機器翻譯中的應用十分廣泛。注意力機制在神經機器翻譯(NMT)模型中通常扮演着統計機器翻譯(SMT)中的對齊機制(Ali
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相關文章
1.
【論文閱讀】Addressing the RareWord Problem in NeuralMachine Translation
2.
【論文】on the properties of neural machine translation :Encoder-decoder approaches 閱讀筆記
3.
論文閱讀——Toward Making the Most of Context in Neural Machine Translation
4.
論文解讀:Selective Attention for Context-aware Neural Machine Translation
5.
論文閱讀:ByteNet, Neural Machine Translation in Linear Time
6.
Neural machine translation by jointly learning to align and translate論文閱讀筆記
7.
attention model--Neural machine translation by jointly learning to align and translate論文解讀
8.
論文解讀:Multimodal Machine Translation with Embedding Prediction
9.
Paper:Effective Approaches to Attention-based Neural Machine Translation
10.
【論文閱讀】Neural Machine Translation by Jointly Learning to Align and Translate
>>更多相關文章<<