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Introduction
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Classroom Contents
CMU Advanced NLP: Bias and Fairness
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- 1 Introduction
- 2 NLP Systems
- 3 Allocational Harm
- 4 Stereotyping
- 5 Bias in human annotation
- 6 Bias detection techniques
- 7 Word embedding association test
- 8 Null hypothesis
- 9 Word embeddings
- 10 Sentence embeddings
- 11 Error rates
- 12 Difference by city
- 13 Language disparities
- 14 Counterfactual evaluation
- 15 Mitigating biases
- 16 Feature and variant rep representations
- 17 Bias sentence embeddings
- 18 Soft devices
- 19 Data augmentation
- 20 Augmentation with humans
- 21 Bias research
