arXiv Machine Learning July 28, 2026 By Chengyao Yu, Hongxin Wei, Bingyi Jing

Robust Conformalized Selection with Noisy Responses

Read the original on arXiv Machine Learning →

arXiv:2607. 22985v1 Announce Type: cross Abstract: Conformalized selection has been widely applied to select high-quality candidates from large datasets with rigorous uncertainty quantification, such as reliable labeling, drug discovery, and the alignment of large language models.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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Denoised Conformal Alignment for Reliable Selection of Conditional Average Treatment Effect Predictions

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