ARTICLEEffective Approaches to Attention-based Neural Machine Translation
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Covers: theory of neural machine translation
Estimated time needed to finish: 60 minutes
Questions this item addresses:
  • 1- What is global attention?
  • 2- What are the implementation problems with global attention?
  • 3- What is local attention and how does it differ from local attention?
  • 4- What are practical alignment functions and how do they perform with attention?
How to use this item?

Read the entire paper

URL: https://arxiv.org/pdf/1508.04025.pdf
Author(s) / creator(s) / reference(s)
Luong et.al
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Effective Approaches to Attention-based Neural Machine Translation

Collaborators
Total time needed: ~2 hours
Objectives
Local and global attention in machine translation
Potential Use Cases
attention based neural translation
Who is this for ?
INTERMEDIATE
Click on each of the following annotated items to see details.
ARTICLE 1. How Does Attention Work in Encoder-Decoder Recurrent Neural Networks
  • 1- What is alignment?
  • How is alignment different from translation?
3 minutes
ARTICLE 2. Global vs. Local Attention
  • 1- What's the difference between global and local attention?
2 minutes
ARTICLE 3. Effective Approaches to Attention-based Neural Machine Translation
  • 1- What is global attention?
  • 2- What are the implementation problems with global attention?
  • 3- What is local attention and how does it differ from local attention?
  • 4- What are practical alignment functions and how do they perform with attention?
60 minutes

Concepts Covered

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