Papers with amplification

1 papers
The Bias Amplification Paradox in Text-to-Image Generation (2024.naacl-long)

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Challenge: amplification is a phenomenon in which models exacerbate biases or stereotypes in training data.
Approach: They compare gender ratios in training vs. generated images to investigate bias amplification . they find that a model amplifys gender-occupation biases considerably .
Outcome: The proposed model amplifys gender-occupation biases in training data, but it can be attributed to discrepancies between training captions and model prompts.

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