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Counterfactual fairness estimates in clinical LLMs can be misleading without a clear understanding of per-action instability, which can vary dramatically across decisions.
Mondrian CP can boost minority-class coverage by over 60% while cutting decision costs in high-stakes scenarios.
LLM agents show no significant demographic bias in decision-making when rigorous statistical methods are applied, challenging assumptions about their fairness.
