論文 Non-Parametric Adaptation for Neural Machine Translation閱讀筆記
這篇論文參考了Encoding Gated Translation Memory into Neural Machine Translation。建議先閱讀這篇論文之後再閱讀本論文。 傳統的NMT（Neural machine translation）模型的泛化能力很強，但是對於專業領域的翻譯或者罕見詞彙的翻譯就不那麼準確了。如何解決這個問題？本文作者是這樣做的，在decoder階段加入一些具有專
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相關文章
- 1. Neural machine translation by jointly learning to align and translate論文閱讀筆記
- 2. [論文閱讀筆記] Massive Exploration of Neural Machine Translation Architectures
- 3. 【論文】on the properties of neural machine translation :Encoder-decoder approaches 閱讀筆記
- 4. 論文閱讀——Dual Learning for Machine Translation
- 5. 論文閱讀：Dual Learning for Machine Translation
- 6. 論文閱讀——Modeling Future Cost for Neural Machine Translation
- 7. 【論文閱讀】Prior Knowledge Integration for Neural Machine Translation using Posterior Regularization
- 8. 論文閱讀：Fast Lexically Constrained Decoding with Dynamic Beam Allocation for Neural Machine Translation
- 9. 文獻閱讀筆記：Phrase-Based & Neural Unsupervised Machine Translation
- 10. Fine-Grained Attention Mechanism for Neural Machine Translation 論文筆記