CMU Multilingual NLP 2020 - Multilingual Training and Cross-Lingual Transfer

CMU Multilingual NLP 2020 - Multilingual Training and Cross-Lingual Transfer

Graham Neubig via YouTube Direct link

evaluation

22 of 23

22 of 23

evaluation

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CMU Multilingual NLP 2020 - Multilingual Training and Cross-Lingual Transfer

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  1. 1 Many languages are left behind
  2. 2 Roadmap
  3. 3 Cross-lingual transfer
  4. 4 Supporting multiple languages could be tedious
  5. 5 Combining the two methods
  6. 6 Use case: covid-19 response
  7. 7 Rapid adaptation of massive multilingual models
  8. 8 Meta-learning for multilingual training
  9. 9 Multilingual NMT
  10. 10 Improve zero-shot NMT
  11. 11 Align multilingual representation
  12. 12 Zero-shot transfer for pretrained representations
  13. 13 Massively multilingual training
  14. 14 Training data highly imbalanced
  15. 15 Heuristic Sampling of Data
  16. 16 Learning to balance data
  17. 17 Problem: sometimes underperforms bilingual model
  18. 18 Multilingual Knowledge Distillation
  19. 19 Adding Language-specific layers
  20. 20 Problem: one-to-many transfer
  21. 21 Problem: multilingual
  22. 22 evaluation
  23. 23 Discussion question

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