mlsanityData to 7 Oct 2026

Self-Calibrating Conformal Prediction

arXiv 2402.07307 ↗First posted 11 Feb 2024stat.ML cs.LG stat.MEcited by 16

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Abstract (arXiv)

In machine learning, model calibration and predictive inference are essential for producing reliable predictions and quantifying uncertainty to support decision-making. Recognizing the complementary roles of point and interval predictions, we introduce Self-Calibrating Conformal Prediction, a method that combines Venn-Abers calibration and conformal prediction to deliver calibrated point predictions alongside prediction intervals with finite-sample validity conditional on these predictions. To achieve this, we extend the original Venn-Abers procedure from binary classification to regression. Our theoretical framework supports analyzing conformal prediction methods that involve calibrating model predictions and subsequently constructing conditionally valid prediction intervals on the same data, where the conditioning set or conformity scores may depend on the calibrated predictions. Real-data experiments show that our method improves interval efficiency through model calibration and offers a practical alternative to feature-conditional validity.

Key facts. Cited by 16 papers in the map (data through 7 Oct 2026). Builds on 19 of its 66 references that are in the map. First posted on arXiv 11 Feb 2024.

Builds on

19 of 66 references.

References · 19

  1. 2016XGBoost: A Scalable Tree Boosting Systemcited by 5,120
  2. 2017On Calibration of Modern Neural Networkscited by 4,860
  3. 2016Distribution-Free Predictive Inference For Regressioncited by 657
  4. 2019Conformalized Quantile Regressioncited by 620
  5. 2020Uncertainty Sets for Image Classifiers using Conformal Predictioncited by 365
  6. 2015ranger: A Fast Implementation of Random Forests for High Dimensional Data in C++ and Rcited by 171
  7. 2023Conformal Prediction With Conditional Guaranteescited by 146
  8. 2021Localized Conformal Prediction: A Generalized Inference Framework for Conformal Predictioncited by 112
  9. 2023Class-Conditional Conformal Prediction with Many Classescited by 109
  10. 2020Distribution-free binary classification: prediction sets, confidence intervals and calibrationcited by 79
  11. 2018Fairness and Accountability Design Needs for Algorithmic Support in High-Stakes Public Sector Decision-Makingcited by 66
  12. 2022Batch Multivalid Conformal Predictioncited by 66
7 more
  1. 2022Practical Adversarial Multivalid Conformal Predictioncited by 65
  2. 2021Distribution-free calibration guarantees for histogram binning without sample splittingcited by 44
  3. 2023High-Dimensional Prediction for Sequential Decision Makingcited by 41
  4. 2023Causal isotonic calibration for heterogeneous treatment effectscited by 16
  5. 2022Calibration Error for Heterogeneous Treatment Effectscited by 5
  6. 2020Confidence intervals for multiple isotonic regression and other monotone modelscited by 3
  7. 2023Well-Calibrated Probabilistic Predictive Maintenance using Venn-Aberscited by 3

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 3; 2025: 6; 2026: 7.

16 papers.

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  1. 2025Decision Theoretic Foundations for Conformal Prediction: Optimal Uncertainty Quantification for Risk-Averse Agentscited by 37
  2. 2025Seeing and Reasoning with Confidence: Supercharging Multimodal LLMs with an Uncertainty-Aware Agentic Frameworkcited by 12
  3. 2024Stabilized Inverse Probability Weighting via Isotonic Calibrationcited by 8
  4. 2025Generalized Venn and Venn-Abers Calibration with Applications in Conformal Predictioncited by 6
  5. 2024Adaptive Uncertainty Quantification for Generative AIcited by 4
  6. 2024Improving the Finite Sample Estimation of Average Treatment Effects using Double/Debiased Machine Learning with Propensity Score Calibrationcited by 4
  7. 2026Calibrate, Don't Curate: Label-Efficient Estimation from Noisy LLM Judgescited by 4
  8. 2026Uncertainty-Aware Reward Modeling for Stable RLHFcited by 4
  9. 2025CLAPS: Aleatoric-Epistemic Scaling via Last-Layer Laplace for Conformal Regressioncited by 2
  10. 2025Bellman Calibration for V-Learning in Offline Reinforcement Learningcited by 2
  11. 2025Extending Prediction-Powered Inference through Conformal Predictioncited by 1
  12. 2026Conformal Risk-Averse Decision Making with Action Conditional Guaranteecited by 1
4 more
  1. 2026Leverage-Weighted Conformal Predictioncited by 0
  2. 2026Inductive Venn-Abers and related regressorscited by 0
  3. 2026Don't Collapse Your Features: Why CenterLoss Hurts OOD Detection and Multi-Scale Mahalanobis Winscited by 0
  4. 2026PICPIs: Prediction-Interval-Conditional Prediction Intervalscited by 0