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