论文笔记：Beam Search Strategies for Neural Machine Translation

时间 2021-01-02

标签 NMT Beam Search 繁體版

原文原文链接

作者： Markus Freitag and Yaser Al-Onaizan 单位： IBM T.J. Watson Research Center 关键词： Beam search; Pruning strategies 问题：束搜索算法跟踪k个状态，而不仅仅只跟踪一个。它从k个随机生成的状态开始，在每一步中都生成所有k个状态的所有后继者。如果这其中的任何一个后继者是目标，那么算法就会停止。

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1. 论文阅读：Fast Lexically Constrained Decoding with Dynamic Beam Allocation for Neural Machine Translation
2. 论文 Non-Parametric Adaptation for Neural Machine Translation阅读笔记
3. Fine-Grained Attention Mechanism for Neural Machine Translation 论文笔记
4. Sampled Softmax 论文笔记：On Using Very Large Target Vocabulary for Neural Machine Translation
5. Neural machine translation by jointly learning to align and translate论文阅读笔记
6. 【论文】on the properties of neural machine translation :Encoder-decoder approaches 阅读笔记
7. [论文阅读笔记] Massive Exploration of Neural Machine Translation Architectures
8. 论文笔记(attention 1)----NEURAL MACHINE TRANSLATION BY JOINTLY LEARNING TO ALIGN AND TRANSLATE
9. 【论文笔记】Effective Approaches to Attention-based Neural Machine Translation
10. 论文笔记(Attention 2)-----Effective Approaches to Attention-based Neural Machine Translation

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