The Future of Natural Language Processing

The Future of Natural Language Processing

Hugging Face via YouTube Direct link

Reporting and evaluation issues

11 of 13

11 of 13

Reporting and evaluation issues

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The Future of Natural Language Processing

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  1. 1 Intro
  2. 2 Open questions, current trends, limits
  3. 3 Model size and Computational efficiency
  4. 4 Using more and more data
  5. 5 Pretraining on more data
  6. 6 Fine-tuning on more data
  7. 7 More data or better models
  8. 8 In-domain vs. out-of-domain generalization
  9. 9 The limits of NLU and the rise of NLG
  10. 10 Solutions to the lack of robustness
  11. 11 Reporting and evaluation issues
  12. 12 The inductive bias question
  13. 13 The common sense question

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