Completed
Fine grained analysis of sentence embeddings
Class Central Classrooms beta
YouTube videos curated by Class Central.
Classroom Contents
CMU Neural Nets for NLP - Model Interpretation
Automatically move to the next video in the Classroom when playback concludes
- 1 Intro
- 2 Why interpretability?
- 3 Dictionary definition
- 4 Two broad themes
- 5 Comparing two directions
- 6 Source Syntax in NMT
- 7 Why neural translations are the right length?
- 8 Fine grained analysis of sentence embeddings
- 9 What you can cram into a single vector: Probing sentence embeddings for linguistic properties
- 10 How to evaluate?
- 11 Automatic evaluation
- 12 Explanation Technique: Influence Functions
- 13 Explanation Techniques: gradient based importance scores
- 14 Explanation Technique: Extractive Rationale Generation
- 15 Future Directions
