arXiv Machine Learning July 14, 2026 By Jungbin Jun, Ilsang Ohn

Online conformal inference with retrospective adjustment for faster adaptation to distribution shift

Read the original on arXiv Machine Learning →

arXiv:2511. 04275v2 Announce Type: replace-cross Abstract: Conformal prediction has emerged as a powerful framework for constructing distribution-free prediction sets with guaranteed coverage assuming only the exchangeability assumption.

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

arXiv Machine Learning

Jul 20

Improving Backward Conformal Prediction via Non-Conformity Score Transformation

arXiv:2602. 01733v3 Announce Type: replace-cross Abstract: Conformal Prediction (CP) provides a statistical framework for uncertainty quantification that constructs prediction sets with coverage guarantees.

By Junxian Liu, Hao Zeng, Hongxin Wei

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Jul 1

Accelerating Conformal Prediction via Approximate Leave-One-Out

arXiv:2606. 31915v1 Announce Type: cross Abstract: While conformal prediction provides a general framework for uncertainty quantification in predictive inference, its application is often limited by computational cost.

By Jiachen Cong, Jingbo Liu

arXiv Machine Learning

Jun 16

Spectral Adaptive Conformal Prediction for Structured Non-Exchangeable Data

arXiv:2606. 15950v1 Announce Type: cross Abstract: Conformal prediction gives prediction intervals with finite-sample coverage when the data are exchangeable.

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arXiv Machine Learning

Jun 16

Audited Conformal Prediction for Classification under Unknown Distribution Shift

arXiv:2606. 14909v1 Announce Type: cross Abstract: We consider the problem of uncertainty quantification for a pretrained classification model deployed under unknown distribution shift.

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arXiv Machine Learning

Jun 11

Coverage Guarantees for Pseudo-Calibrated Conformal Prediction under Distribution Shift

arXiv:2602. 14913v2 Announce Type: replace Abstract: Conformal prediction (CP) offers distribution-free marginal coverage guarantees under an exchangeability assumption, but these guarantees can fail if the data distribution shifts.

By Farbod Siahkali, Ashwin Verma, Vijay Gupta

fine-tuning

arXiv Machine Learning

Jun 17

Questioning the Coverage-Length Metric in Conformal Prediction: When Shorter Intervals Are Not Better

arXiv:2601. 21455v2 Announce Type: replace-cross Abstract: Conformal prediction(CP) has become a cornerstone of distribution-free uncertainty quantification, conventionally evaluated by its coverage and interval length.

By Yizhou Min, Yizhou Lu, Lanqi Li, Zhen Zhang, Jiaye Teng

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Improving Backward Conformal Prediction via Non-Conformity Score Transformation

Accelerating Conformal Prediction via Approximate Leave-One-Out

Spectral Adaptive Conformal Prediction for Structured Non-Exchangeable Data

Audited Conformal Prediction for Classification under Unknown Distribution Shift

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Questioning the Coverage-Length Metric in Conformal Prediction: When Shorter Intervals Are Not Better