We extend conformal prediction to control the expected value of any monotone loss function. The algorithm generalizes split conformal prediction together with its coverage guarantee. Like conformal prediction, the conformal risk control procedure is tight up to an $\mathcal{O}(1/n)$ factor. Worked examples from computer vision and natural language processing demonstrate the usage of our algorithm to bound the false negative rate, graph distance, and token-level F1-score.

中文翻译：

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适形风险控制

我们扩展保形预测来控制任何单调损失函数的期望值。该算法将分割保形预测与其覆盖保证一起推广。与保形预测一样，保形风险控制过程严格到$\mathcal{O}(1/n)$ 因子。来自计算机视觉和自然语言处理的工作示例展示了我们的算法用于限制假阴性率、图距离和令牌级 F1 分数。