mlsanityData to 14 Oct 2026

A Generic Framework for Conformal Fairness

arXiv 2505.16115 ↗First posted 22 May 2025cs.LGcited by 7

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Abstract (arXiv)

Conformal Prediction (CP) is a popular method for uncertainty quantification with machine learning models. While conformal prediction provides probabilistic guarantees regarding the coverage of the true label, these guarantees are agnostic to the presence of sensitive attributes within the dataset. In this work, we formalize textitConformal Fairness, a notion of fairness using conformal predictors, and provide a theoretically well-founded algorithm and associated framework to control for the gaps in coverage between different sensitive groups. Our framework leverages the exchangeability assumption (implicit to CP) rather than the typical IID assumption, allowing us to apply the notion of Conformal Fairness to data types and tasks that are not IID, such as graph data. Experiments were conducted on graph and tabular datasets to demonstrate that the algorithm can control fairness-related gaps in addition to coverage aligned with theoretical expectations.

Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). Builds on 33 of its 47 references that are in the map. First posted on arXiv 22 May 2025.

Builds on

33 of 47 references.

References · 33

  1. 2016Semi-Supervised Classification with Graph Convolutional Networkscited by 11,361
  2. 2017Graph Attention Networkscited by 8,923
  3. 2017Inductive Representation Learning on Large Graphscited by 6,320
  4. 2016XGBoost: A Scalable Tree Boosting Systemcited by 5,166
  5. 2019A Survey on Bias and Fairness in Machine Learningcited by 1,917
  6. 2021A Gentle Introduction to Conformal Prediction and Distribution-Free Uncertainty Quantificationcited by 792
  7. 2014Certifying and removing disparate impactcited by 715
  8. 2016Distribution-Free Predictive Inference For Regressioncited by 668
  9. 2019Conformalized Quantile Regressioncited by 629
  10. 2021Retiring Adult: New Datasets for Fair Machine Learningcited by 449
  11. 2020Classification with Valid and Adaptive Coveragecited by 396
  12. 2018Tune: A Research Platform for Distributed Model Selection and Trainingcited by 395
21 more
  1. 2020Uncertainty Sets for Image Classifiers using Conformal Predictioncited by 366
  2. 2016Least Ambiguous Set-Valued Classifiers with Bounded Error Levelscited by 272
  3. 2019Flexibly Fair Representation Learning by Disentanglementcited by 196
  4. 2023Conformal Prediction With Conditional Guaranteescited by 152
  5. 2021Towards a Unified Framework for Fair and Stable Graph Representation Learningcited by 128
  6. 2023Class-Conditional Conformal Prediction with Many Classescited by 109
  7. 2023Uncertainty Quantification over Graph with Conformalized Graph Neural Networkscited by 79
  8. 2022Fairness in Graph Mining: A Surveycited by 76
  9. 2021Fair Conformal Predictors for Applications in Medical Imagingcited by 74
  10. 2022Batch Multivalid Conformal Predictioncited by 67
  11. 2022Practical Adversarial Multivalid Conformal Predictioncited by 65
  12. 2018Residual Unfairness in Fair Machine Learning from Prejudiced Datacited by 49
  13. 2022Active Fairness Auditingcited by 27
  14. 2020Justicia: A Stochastic SAT Approach to Formally Verify Fairnesscited by 25
  15. 2022Conformalized Fairness via Quantile Regressioncited by 19
  16. 2023HappyMap: A Generalized Multi-calibration Methodcited by 18
  17. 2023Equal Opportunity of Coverage in Fair Regressioncited by 16
  18. 2022FairEGM: Fair Link Prediction and Recommendation via Emulated Graph Modificationcited by 15
  19. 2023Learning Optimal Fair Scoring Systems for Multi-Class Classificationcited by 8
  20. 2023SimFair: A Unified Framework for Fairness-Aware Multi-Label Classificationcited by 7
  21. 2022FairMILE: Towards an Efficient Framework for Fair Graph Representation Learningcited by 4

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 2; 2026: 5.

7 papers.

  1. 2025FedCF: Fair Federated Conformal Predictioncited by 3
  2. 2025Counterfactually Fair Conformal Predictioncited by 2
  3. 2026Beyond Procedure: Substantive Fairness in Conformal Predictioncited by 2
  4. 2026On the Burden of Achieving Fairness in Conformal Predictioncited by 1
  5. 2026Fair Conformal Classification via Learning Representation-Based Groupscited by 0
  6. 2026Unifying Conformal Language Tasks with In-Context Ensemblescited by 0
  7. 2026SimplexUQ: An Evaluation Framework and Benchmark for Conformal Uncertainty on Simplex-Valued Predictionscited by 0