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Trajectory-Guided Steering: Mitigating Spurious Feature Bias in Clinical Classification

Sakib, Fardin Ahsan et al.
arXiv (All) · Papers
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computation-and-language
Large language models rely on spurious features in clinical classification: swapping a single gender token in clinical notes alters gender-irrelevant diagnoses in up to 53.5% of cases. Existing inference-time corrections either need counterfactual data built around the specific spurious feature or b
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