Research map / Label-efficient and robust learning / Recognition and long-tail
Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Apply hard debiasing | w2vNEWS · she-he analogy generation | analogies judged stereotypical by majority: 19% -> 6% | Helped |
| Apply hard debiasing | w2vNEWS · RG | score: 62.3 -> 62.4 | No clear effect |
| Apply hard debiasing | w2vNEWS · WS | score: 54.5 -> 54.1 | No clear effect |
| Apply hard debiasing | w2vNEWS · MSR-analogy | analogy score: 57.0 -> 57.0 | No clear effect |
| Apply soft debiasing | w2vNEWS · RG | score: 62.3 -> 62.4 | No clear effect |
| Apply soft debiasing | w2vNEWS · WS | score: 54.5 -> 54.2 | No clear effect |
| Apply soft debiasing | w2vNEWS · MSR-analogy | analogy score: 57.0 -> 56.8 | No clear effect |
| Use soft rather than hard debiasing | w2vNEWS · gender stereotype reduction | stereotypical analogy reduction | Hurt |
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