Papers by Diego Fernandez Slezak
On the Interpretability and Significance of Bias Metrics in Texts: a PMI-based Approach (2023.acl-short)
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| Challenge: | Word embeddings have been used to quantify biases in texts for years, but their statistical properties and advantages have not been studied. |
| Approach: | They propose to use PMI-based metric to quantify bias in corpora by conditional probabilities and odds ratio to approximate it. |
| Outcome: | The proposed measure can be approximated by an odds ratio, which makes statistical inferences cost-effective and meaningful. |
The Undesirable Dependence on Frequency of Gender Bias Metrics Based on Word Embeddings (2022.findings-emnlp)
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| Challenge: | Recent studies have found word embeddings can capture semantic similarity but may be affected by word frequency. |
| Approach: | They find that word embeddings can capture semantic similarity but may be affected by word frequency . they compare this effect with an alternative metric based on Pointwise Mutual Information . |
| Outcome: | The proposed method does not depend on word frequency, but it does return female bias in low frequency words. |