AINeutralarXiv – CS AI · 6h ago7/10
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DeFrame: Debiasing Large Language Models Against Framing Effects
Researchers identify 'framing disparity' as a hidden source of bias in large language models, where semantically equivalent prompts expressed differently produce inconsistent fairness outcomes. The study proposes DeFrame, a debiasing method that improves LLM consistency across alternative framings, addressing a gap between standard fairness evaluations and real-world performance.
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