mlsanityData to 13 Oct 2026

Confidence on the Focal: Conformal Prediction with Selection-Conditional Coverage

arXiv 2403.03868 ↗First posted 6 Mar 2024stat.ME math.ST stat.MLcited by 14

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Abstract (arXiv)

Conformal prediction builds marginally valid prediction intervals that cover the unknown outcome of a randomly drawn test point with a prescribed probability. However, in practice, data-driven methods are often used to identify specific test unit(s) of interest, requiring uncertainty quantification tailored to these focal units. In such cases, marginally valid conformal prediction intervals may fail to provide valid coverage for the focal unit(s) due to selection bias. This paper presents a general framework for constructing a prediction set with finite-sample exact coverage, conditional on the unit being selected by a given procedure. The general form of our method accommodates arbitrary selection rules that are invariant to the permutation of the calibration units, and generalizes Mondrian Conformal Prediction to multiple test units and non-equivariant classifiers. We also work out computationally efficient implementation of our framework for a number of realistic selection rules, including top-K selection, optimization-based selection, selection based on conformal p-values, and selection based on properties of preliminary conformal prediction sets. The performance of our methods is demonstrated via applications in drug discovery and health risk prediction.

Key facts. Cited by 14 papers in the map (data through 13 Oct 2026). Builds on 24 of its 58 references that are in the map. First posted on arXiv 6 Mar 2024.

Builds on

24 of 58 references.

References · 24

  1. 2021A Gentle Introduction to Conformal Prediction and Distribution-Free Uncertainty Quantificationcited by 786
  2. 2016Distribution-Free Predictive Inference For Regressioncited by 660
  3. 2019Conformalized Quantile Regressioncited by 625
  4. 2020Classification with Valid and Adaptive Coveragecited by 393
  5. 2023Robots That Ask For Help: Uncertainty Alignment for Large Language Model Plannerscited by 302
  6. 2021Testing for Outliers with Conformal p-valuescited by 133
  7. 2013Exact post-selection inference, with application to the lassocited by 90
  8. 2022Selection by Prediction with Conformal p-valuescited by 68
  9. 2014Exact Post-Selection Inference for Sequential Regression Procedurescited by 47
  10. 2022An Extensive Data Processing Pipeline for MIMIC-IVcited by 39
  11. 2023Model-free selective inference under covariate shift via weighted conformal p-valuescited by 27
  12. 2022Integrative conformal p-values for powerful out-of-distribution testing with labeled outlierscited by 19
12 more
  1. 2023Derandomized Novelty Detection with FDR Control via Conformal E-valuescited by 15
  2. 2022Post-selection inference for e-value based confidence intervalscited by 14
  3. 2023Conformal Drug Property Prediction with Density Estimation under Covariate Shiftcited by 13
  4. 2019Online Control of the False Coverage Rate and False Sign Ratecited by 11
  5. 2023Selective conformal inference with false coverage-statement rate controlcited by 11
  6. 2017Unifying approach to selective inference with applications to cross-validationcited by 8
  7. 2020A (tight) upper bound for the length of confidence intervals with conditional coveragecited by 5
  8. 2023Post-selection Inference for Conformal Prediction: Trading off Coverage for Precisioncited by 5
  9. 2024Conformalized Selective Regressioncited by 4
  10. 2014Post-selection point and interval estimation of signal sizes in Gaussian samplescited by 3
  11. 2023An Exact Sampler for Inference after Polyhedral Model Selectioncited by 2
  12. 2020Hybrid Confidence Intervals for Informative Uniform Asymptotic Inference After Model Selectioncited by 1

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Cited by year (2026 to 13 Oct)

Citing papers per year: 2024: 4; 2025: 4; 2026: 6.

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  1. 2024Conformal Prediction for Natural Language Processing: A Surveycited by 52
  2. 2024Conformal Alignment: Knowing When to Trust Foundation Models with Guaranteescited by 52
  3. 2024Selecting informative conformal prediction sets with false coverage rate controlcited by 7
  4. 2026A Joint Finite-Sample Certificate for Adaptive Selective Conformal Risk Controlcited by 5
  5. 2024Powerful batch conformal prediction for classificationcited by 4
  6. 2025Calibrated Predictive Lower Bounds on Time-to-Unsafe-Sampling in LLMscited by 3
  7. 2025Online Conformal Selection with Accept-to-Reject Changescited by 2
  8. 2025Dual-Splitting Conformal Prediction for Multi-Step Time Series Forecastingcited by 1
  9. 2026Elements of Conformal Predictioncited by 1
  10. 2026Conformal Risk-Averse Decision Making with Action Conditional Guaranteecited by 1
  11. 2025Quantifying and Improving Adaptivity in Conformal Prediction through Input Transformationscited by 0
  12. 2026Online Selective Conformal Prediction with Asymmetric Rules: A Permutation Test Approachcited by 0
2 more
  1. 2026Goal-Oriented Lower-Tail Calibration of Gaussian Processes for Bayesian Optimizationcited by 0
  2. 2026When May a Model Replace the Experiment? Audits, Licenses, and the Price of Trust in Surrogate-Driven Designcited by 0