Neural Nets for NLP 2020: Advanced Search Algorithms

Neural Nets for NLP 2020: Advanced Search Algorithms

Graham Neubig via YouTube Direct link

The Generation Problem

2 of 14

2 of 14

The Generation Problem

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Neural Nets for NLP 2020: Advanced Search Algorithms

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  1. 1 Intro
  2. 2 The Generation Problem
  3. 3 Ancestral Sampling
  4. 4 Why do we Search?
  5. 5 Search Errors, Model Errors example from Neubig (2015) • Search error: the search algorithm fails to find an output that optimizes its search criterion . Model error: the output that optimizes the se…
  6. 6 What beam size should I use?
  7. 7 Better Search can Hurt Results! (Koehn and Knowles 2017)
  8. 8 How to Fix Model Errors?
  9. 9 Minimum Bayes Risk Reranking
  10. 10 Improving Diversity in top N Choices
  11. 11 A Typical Model Error: Length Bias
  12. 12 Length Normalization
  13. 13 Predict the output length (Eriguchi et al. 2016)
  14. 14 Cautions about Sampling- based Search · Is sampling necessary for diversity?: questionable, we could do diverse beam search instead

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