Papers with bias mitigation strategy
White Men Lead, Black Women Help? Benchmarking and Mitigating Language Agency Social Biases in LLMs (2025.acl-long)
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| Challenge: | Social biases manifest in language agency, but there is no comprehensive benchmark for evaluating such biase in language models. |
| Approach: | They propose a benchmark to evaluate language agency biases in large language models . they propose 'Mitigation via Selective Rewrite' to selectively revise parts of generated texts . |
| Outcome: | The proposed language agency bias evaluation benchmark identifies gender, racial, and intersectional biases in 3 recent LLMs. |
Aligned but Blind: Alignment Increases Implicit Bias by Reducing Awareness of Race (2025.acl-long)
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| Challenge: | et al., 2012) show value-aligned language models exhibit stereotypes in word association tasks . ignoring racial nuances can perpetuate subtle biases in LMs . |
| Approach: | They propose a bias mitigation strategy that incentivizes representation of racial concepts in early model layers. |
| Outcome: | The proposed approach incentivizes representation of racial concepts in early model layers . it reduces implicit bias by reducing the number of ambiguous inputs, the authors show . |