Fairness Metrics papers, 2023–2026

Key findings

• Fairness Metrics went from 78 papers in 2023 to 78 in 2026, roughly 1.0x in three years.
• NeurIPS publishes the most Fairness Metrics work: 137 papers from 2023 to 2026, 37% of the four-venue total.
• The fastest-growing overlap is with Alignment and Safety: papers tagged with both rose from 3 in 2023 to 18 in 2026.
• Among the 5 topics under Causal and Fairness, it ranks #3 by 2026 paper count; the fastest grower in the group, Causal Discovery, is up 2.4x versus 1.0x here.

Representative papers

Spread across years and venues so every edition shows up

• NeurIPS 2026Adversarial Group Fairness in Contextual Bandits: When Robust is Not Fair
• ICML 2026Capacitated Fair-Range Clustering: Hardness and Approximation Algorithms
• ICLR 2026Fairness-Aware Multi-view Evidential Learning with Adaptive Prior
• CVPR 2026EMMA Concept Erasure Benchmark with Comprehensive Semantic Metrics and Diverse
• NeurIPS 2025Analyzing Similarity Metrics for Data Selection for Language Model Pretraining
• ICML 2025Kernel Quantile Embeddings and Associated Probability Metrics
• ICLR 2025Expected Sliced Transport Plans
• CVPR 2025Flexible Group Count Enables Hassle-Free Structured Pruning
• NeurIPS 2024ABCFair: an Adaptable Benchmark approach for Comparing Fairness Methods
• ICML 2024Centralized Selection with Preferences in the Presence of Biases
• ICLR 2024Causal Fairness under Unobserved Confounding: A Neural Sensitivity Framework
• CVPR 2024GARField: Group Anything with Radiance Fields
• NeurIPS 2023[Re] Fairness Guarantees under Demographic Shift
• ICML 2023A Toy Model of Universality: Reverse Engineering how Networks Learn Group Operations
• ICLR 2023Confidential-PROFITT: Confidential PROof of FaIr Training of Trees
• CVPR 2023Improving Fairness in Facial Albedo Estimation via Visual-Textual Cues
• NeurIPS 2026Auditing Cross-Lingual Fairness in Language Model Watermarking
• ICML 2026Fine-to-Coarse Fairness-Informed Multi-View Clustering
• ICLR 2026Fast and Stable Riemannian Metrics on SPD Manifolds via Cholesky Product Geometry
• CVPR 2026Decoupling Bias Aligning Distributions Synergistic Fairness Optimization for Deepfake Detection

All Fairness Metrics papers

118 papers, page 2 of 3

51. ICML 2024FairProof : Confidential and Certifiable Fairness for Neural Networks
52. ICML 2024FRAPPÉ: A Group Fairness Framework for Post-Processing Everything
53. ICML 2024Grokking Group Multiplication with Cosets
54. ICML 2024Hierarchical Integral Probability Metrics: A distance on random probability measures with low sample complexity
55. ICML 2024How Far Can Fairness Constraints Help Recover From Biased Data?
56. ICML 2024Improving Group Robustness on Spurious Correlation Requires Preciser Group Inference
57. ICML 2024Individual Fairness in Graph Decomposition
58. ICML 2024Monotone Individual Fairness
59. ICML 2024On The Fairness Impacts of Hardware Selection in Machine Learning
60. ICML 2024On the Maximal Local Disparity of Fairness-Aware Classifiers
61. ICML 2024PairNet: Training with Observed Pairs to Estimate Individual Treatment Effect
62. ICML 2024Position: Scarce Resource Allocations That Rely On Machine Learning Should Be Randomized
63. ICML 2024Promoting External and Internal Equities Under Ex-Ante/Ex-Post Metrics in Online Resource Allocation
64. ICML 2024Remembering to Be Fair: Non-Markovian Fairness in Sequential Decision Making
65. ICML 2024Size-invariance Matters: Rethinking Metrics and Losses for Imbalanced Multi-object Salient Object Detection
66. ICML 2024Stability and Multigroup Fairness in Ranking with Uncertain Predictions
67. ICML 2024Standardized Interpretable Fairness Measures for Continuous Risk Scores
68. ICML 2024Variational Partial Group Convolutions for Input-Aware Partial Equivariance of Rotations and Color-Shifts
69. NeurIPS 2024ABCFair: an Adaptable Benchmark approach for Comparing Fairness Methods
70. NeurIPS 2024Achievable Fairness on Your Data With Utility Guarantees
71. NeurIPS 2024Bisimulation Metrics are Optimal Transport Distances, and Can be Computed Efficiently
72. NeurIPS 2024Counterfactual Fairness by Combining Factual and Counterfactual Predictions
73. NeurIPS 2024CultureLLM: Incorporating Cultural Differences into Large Language Models
74. NeurIPS 2024Do Counterfactually Fair Image Classifiers Satisfy Group Fairness? -- A Theoretical and Empirical Study
75. NeurIPS 2024Does Egalitarian Fairness Lead to Instability? The Fairness Bounds in Stable Federated Learning Under Altruistic Behaviors
76. NeurIPS 2024Enhancing Robustness of Last Layer Two-Stage Fair Model Corrections
77. NeurIPS 2024Enriching Disentanglement: From Logical Definitions to Quantitative Metrics
78. NeurIPS 2024Fair Bilevel Neural Network (FairBiNN): On Balancing fairness and accuracy via Stackelberg Equilibrium
79. NeurIPS 2024Fair GLASSO: Estimating Fair Graphical Models with Unbiased Statistical Behavior
80. NeurIPS 2024Fair Kernel K-Means: from Single Kernel to Multiple Kernel
81. NeurIPS 2024Fair Online Bilateral Trade
82. NeurIPS 2024Fair Secretaries with Unfair Predictions
83. NeurIPS 2024Fair Wasserstein Coresets
84. NeurIPS 2024Fairness and Efficiency in Online Class Matching
85. NeurIPS 2024Fairness in Social Influence Maximization via Optimal Transport
86. NeurIPS 2024Fairness without Harm: An Influence-Guided Active Sampling Approach
87. NeurIPS 2024Fairness-Aware Estimation of Graphical Models
88. NeurIPS 2024Fairness-Aware Meta-Learning via Nash Bargaining
89. NeurIPS 2024Graph-based Uncertainty Metrics for Long-form Language Model Generations
90. NeurIPS 2024Improving Adversarial Robust Fairness via Anti-Bias Soft Label Distillation
91. NeurIPS 2024Improving Subgroup Robustness via Data Selection
92. NeurIPS 2024Interpolating Item and User Fairness in Multi-Sided Recommendations
93. NeurIPS 2024Learning to Understand: Identifying Interactions via the Möbius Transform
94. NeurIPS 2024MAGNET: Improving the Multilingual Fairness of Language Models with Adaptive Gradient-Based Tokenization
95. NeurIPS 2024Mind the Graph When Balancing Data for Fairness or Robustness
96. NeurIPS 2024Mitigating Spurious Correlations via Disagreement Probability
97. NeurIPS 2024Monomial Matrix Group Equivariant Neural Functional Networks
98. NeurIPS 2024Multi-Group Proportional Representation in Retrieval
99. NeurIPS 2024Navigating the Maze of Explainable AI: A Systematic Approach to Evaluating Methods and Metrics
100. NeurIPS 2024OxonFair: A Flexible Toolkit for Algorithmic Fairness

FAQ

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

368 in total: 78 in 2023, 118 in 2024, 94 in 2025, 78 in 2026.

How many Fairness Metrics papers are at NeurIPS 2026?

NeurIPS 2026 has 26 Fairness Metrics papers, versus 33 the year before.

How many Fairness Metrics papers are at ICLR 2026?

ICLR 2026 has 27 Fairness Metrics papers, versus 30 the year before.

How many Fairness Metrics papers are at ICML 2026?

ICML 2026 has 17 Fairness Metrics papers, versus 24 the year before.

How many Fairness Metrics papers are at CVPR 2026?

CVPR 2026 has 8 Fairness Metrics papers, versus 7 the year before.

Which conference publishes the most Fairness Metrics papers?

NeurIPS, with 137 papers from 2023 to 2026.