Counterfactual Fairness papers, 2023–2026

Key findings

• Counterfactual Fairness fell from 31 papers in 2023 to 21 in 2026, so interest is cooling.
• NeurIPS publishes the most Counterfactual Fairness work: 39 papers from 2023 to 2026, 38% of the four-venue total.
• The fastest-growing overlap is with Counterfactual Explanation: papers tagged with both rose from 8 in 2023 to 10 in 2026.
• Among the 5 topics under Causal and Fairness, it ranks #5 by 2026 paper count; the fastest grower in the group, Causal Discovery, is up 2.4x versus 0.7x here.

Representative papers

Spread across years and venues so every edition shows up

• NeurIPS 2026CounterFlowNet: From Minimal Changes to Meaningful Counterfactual Explanations
• ICML 2026Density-Guided Robust Counterfactual Explanations on Tabular Data under Model Multiplicity
• ICLR 2026Counterfactual Explanations on Robust Perceptual Geodesics
• NeurIPS 2025Statistical Parity with Exponential Weights
• ICML 2025Causal Logistic Bandits with Counterfactual Fairness Constraints
• ICLR 2025Certifying Counterfactual Bias in LLMs
• NeurIPS 2024Reproducibility Study: Equal Improvability: A New Fairness Notion Considering the Long-Term Impact
• ICML 2024CF-OPT: Counterfactual Explanations for Structured Prediction
• ICLR 2024Counterfactual Density Estimation using Kernel Stein Discrepancies
• CVPR 2024FADES: Fair Disentanglement with Sensitive Relevance
• NeurIPS 2023[Re] Fairness Guarantees under Demographic Shift
• ICML 2023Counterfactual Analysis in Dynamic Latent State Models
• ICLR 2023FairGBM: Gradient Boosting with Fairness Constraints
• CVPR 2023Improving Fairness in Facial Albedo Estimation via Visual-Textual Cues
• NeurIPS 2026Offloading Score: Measuring AI Reliance through Counterfactual Workflows
• ICML 2026The Fairness Hierarchy: A viewpoint from causal inference
• ICLR 2026Counterfactual LLM-based Framework for Measuring Rhetorical Style
• NeurIPS 2025On Hierarchies of Fairness Notions in Cake Cutting: From Proportionality to Super Envy-Freeness
• ICML 2025Counterfactual Graphical Models: Constraints and Inference
• ICLR 2025Towards counterfactual fairness through auxiliary variables

All Counterfactual Fairness papers

102 papers, page 2 of 3

51. ICML 2024CF-OPT: Counterfactual Explanations for Structured Prediction
52. ICML 2024Do Large Code Models Understand Programming Concepts? Counterfactual Analysis for Code Predicates
53. ICML 2024Do Models Explain Themselves? Counterfactual Simulatability of Natural Language Explanations
54. ICML 2024Fair Risk Control: A Generalized Framework for Calibrating Multi-group Fairness Risks
55. ICML 2024FRAPPÉ: A Group Fairness Framework for Post-Processing Everything
56. ICML 2024How Far Can Fairness Constraints Help Recover From Biased Data?
57. ICML 2024Monotone Individual Fairness
58. ICML 2024Refined Coreset Selection: Towards Minimal Coreset Size under Model Performance Constraints
59. ICML 2024Standardized Interpretable Fairness Measures for Continuous Risk Scores
60. NeurIPS 2024ABCFair: an Adaptable Benchmark approach for Comparing Fairness Methods
61. NeurIPS 2024Counterfactual Fairness by Combining Factual and Counterfactual Predictions
62. NeurIPS 2024Do Counterfactually Fair Image Classifiers Satisfy Group Fairness? -- A Theoretical and Empirical Study
63. NeurIPS 2024OxonFair: A Flexible Toolkit for Algorithmic Fairness
64. NeurIPS 2024Proportional Fairness in Non-Centroid Clustering
65. NeurIPS 2024Regression under demographic parity constraints via unlabeled post-processing
66. NeurIPS 2024Reproducibility Study: Equal Improvability: A New Fairness Notion Considering the Long-Term Impact
67. NeurIPS 2024Statistical Inference for Fairness Auditing
68. NeurIPS 2024The Fairness-Quality Tradeoff in Clustering
69. NeurIPS 2024The Fragility of Fairness: Causal Sensitivity Analysis for Fair Machine Learning
70. NeurIPS 2024Towards Harmless Rawlsian Fairness Regardless of Demographic Prior
71. NeurIPS 2024When is Multicalibration Post-Processing Necessary?
72. CVPR 2023Improving Fairness in Facial Albedo Estimation via Visual-Textual Cues
73. CVPR 2023Masked Images Are Counterfactual Samples for Robust Fine-Tuning
74. ICLR 2023FairGBM: Gradient Boosting with Fairness Constraints
75. ICLR 2023FIFA: Making Fairness More Generalizable in Classifiers Trained on Imbalanced Data
76. ICLR 2023Learning with Logical Constraints but without Shortcut Satisfaction
77. ICLR 2023Neural Causal Models for Counterfactual Identification and Estimation
78. ICML 2023Counterfactual Analysis in Dynamic Latent State Models
79. ICML 2023Eventual Discounting Temporal Logic Counterfactual Experience Replay
80. ICML 2023Fairness in Matching under Uncertainty
81. ICML 2023Fairness in Streaming Submodular Maximization over a Matroid Constraint
82. ICML 2023GLOBE-CE: A Translation Based Approach for Global Counterfactual Explanations
83. ICML 2023Improving l1-Certified Robustness via Randomized Smoothing by Leveraging Box Constraints
84. ICML 2023Matrix Estimation for Individual Fairness
85. ICML 2023Robust Counterfactual Explanations for Neural Networks With Probabilistic Guarantees
86. ICML 2023Sequential Counterfactual Risk Minimization
87. ICML 2023Subset Selection Based On Multiple Rankings in the Presence of Bias: Effectiveness of Fairness Constraints for Multiwinner Voting Score Functions
88. ICML 2023Superhuman Fairness
89. ICML 2023Trustworthy Policy Learning under the Counterfactual No-Harm Criterion
90. ICML 2023Weak Proxies are Sufficient and Preferable for Fairness with Missing Sensitive Attributes
91. NeurIPS 2023[Re] Fairness Guarantees under Demographic Shift
92. NeurIPS 2023[Re] FOCUS: Flexible Optimizable Counterfactual Explanations for Tree Ensembles
93. NeurIPS 2023Adapting Fairness Interventions to Missing Values
94. NeurIPS 2023Auditing Fairness by Betting
95. NeurIPS 2023Constant Approximation for Individual Preference Stable Clustering
96. NeurIPS 2023Counterfactually Fair Representation
97. NeurIPS 2023Doubly Constrained Fair Clustering
98. NeurIPS 2023Fairness Aware Counterfactuals for Subgroups
99. NeurIPS 2023Fast Model DeBias with Machine Unlearning
100. NeurIPS 2023Group Fairness in Peer Review

FAQ

How many Counterfactual Fairness papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

102 in total: 31 in 2023, 31 in 2024, 19 in 2025, 21 in 2026.

How many Counterfactual Fairness papers are at NeurIPS 2026?

NeurIPS 2026 has 10 Counterfactual Fairness papers, versus 5 the year before.

How many Counterfactual Fairness papers are at ICLR 2026?

ICLR 2026 has 4 Counterfactual Fairness papers, versus 6 the year before.

How many Counterfactual Fairness papers are at ICML 2026?

ICML 2026 has 7 Counterfactual Fairness papers, versus 8 the year before.

How many Counterfactual Fairness papers are at CVPR 2024?

CVPR 2024 has 3 Counterfactual Fairness papers, versus 2 the year before.

Which conference publishes the most Counterfactual Fairness papers?

NeurIPS, with 39 papers from 2023 to 2026.