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CMU Neural Nets for NLP: Model Interpretation
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- 1 Intro
- 2 Why interpretability?
- 3 What is interpretability?
- 4 Two broad themes
- 5 Source Syntax in NMT
- 6 Why neural translations are the right length?
- 7 Fine grained analysis of sentence embeddings
- 8 What you can cram into a single vector: Probing sentence embeddings for linguistic properties
- 9 Issues with probing
- 10 Minimum Description Length (MDL) Probes
- 11 How to evaluate?
- 12 Explanation Techniques: gradient based importance scores
- 13 Explanation Technique: Extractive Rationale Generation
