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

368 papers, page 2 of 8

51. ICML 2026Sequential Group Composition: A Window into the Mechanics of Deep Learning
52. ICML 2026The Fairness Hierarchy: A viewpoint from causal inference
53. NeurIPS 2026A Comprehensive View of Fairness through Distributional Stability
54. NeurIPS 2026Adversarial Group Fairness in Contextual Bandits: When Robust is Not Fair
55. NeurIPS 2026Auditing Cross-Lingual Fairness in Language Model Watermarking
56. NeurIPS 2026Beyond Proxy Metrics: MLLM-Based Human Surrogate Evaluation for Explainable AI
57. NeurIPS 2026Cost Efficient Fairness Audit Under Partial Feedback
58. NeurIPS 2026Data-Free Metrics Are Not Invariant Under Functionality-Preserving Reparametrisations
59. NeurIPS 2026Faithfulness Metrics Don't Measure Faithfulness: A Meta-Evaluation with Ground Truth
60. NeurIPS 2026Forecasting Downstream Performance of LLMs With Proxy Metrics
61. NeurIPS 2026FRInGe: Distribution-Space Integrated Gradients with Fisher–Rao Geometry
62. NeurIPS 2026Geometry-Aware Similarity Metrics for Neural Representations on Riemannian and Statistical Manifolds
63. NeurIPS 2026How Does Pruning Change Decisions in Large Language Models?
64. NeurIPS 2026Inferring learning rules in deep neural network architectures from animal learning data
65. NeurIPS 2026Malicious Node Injection: A Transferable Adversarial Attack on GNN Fairness
66. NeurIPS 2026Matrix-Free Natural Gradient via Stochastic Truncated Metrics
67. NeurIPS 2026Overcoming the Resolution Limit: Significance-Aware Regularization for Intersectional Fairness
68. NeurIPS 2026Post-Processing Guarantees for Classification under Linear-Fractional Performance Metrics
69. NeurIPS 2026Practical Estimation of the Bayes Optimal Fairness-Accuracy Tradeoff with Soft Labels
70. NeurIPS 2026Recovering Clean Evaluation Metrics from Contaminated Benchmarks
71. NeurIPS 2026Reviewer Scores Are Not Comparable Across Research Areas in ML Peer Review
72. NeurIPS 2026Scalable Fair Learning via Cramér-von Mises Regularization
73. NeurIPS 2026Simultaneous Individual, Group and Multigroup Fairness in Set Covering Problems
74. NeurIPS 2026Space Group Conditional Flow Matching
75. NeurIPS 2026Spectral-Spatial Interpretation
76. NeurIPS 2026Stay Fair! Ensuring Group Fairness in Diffusion Models Across Guidance Scales
77. NeurIPS 2026Strategic Causal Policy Learning: Welfare, Safety, and Fairness Thresholds
78. NeurIPS 2026The Pok\'emon Theorem and other Fairness Impossibility Results
79. CVPR 2025AI-Face: A Million-Scale Demographically Annotated AI-Generated Face Dataset and Fairness Benchmark
80. CVPR 2025AIM-Fair: Advancing Algorithmic Fairness via Selectively Fine-Tuning Biased Models with Contextual Synthetic Data
81. CVPR 2025Data-Free Group-Wise Fully Quantized Winograd Convolution via Learnable Scales
82. CVPR 2025FALCON: Fairness Learning via Contrastive Attention Approach to Continual Semantic Scene Understanding
83. CVPR 2025Flexible Group Count Enables Hassle-Free Structured Pruning
84. CVPR 2025ID-Patch: Robust ID Association for Group Photo Personalization
85. CVPR 2025Revisiting Fairness in Multitask Learning: A Performance-Driven Approach for Variance Reduction
86. ICLR 2025A Generic Framework for Conformal Fairness
87. ICLR 2025A Probabilistic Perspective on Unlearning and Alignment for Large Language Models
88. ICLR 2025An Effective Theory of Bias Amplification
89. ICLR 2025Balancing Bias in Two-sided Markets for Fair Stable Matchings
90. ICLR 2025Bridging Jensen Gap for Max-Min Group Fairness Optimization in Recommendation
91. ICLR 2025CEB: Compositional Evaluation Benchmark for Fairness in Large Language Models
92. ICLR 2025Collapsed Language Models Promote Fairness
93. ICLR 2025Comparing noisy neural population dynamics using optimal transport distances
94. ICLR 2025Competitive Fair Scheduling with Predictions
95. ICLR 2025DarkBench: Benchmarking Dark Patterns in Large Language Models
96. ICLR 2025Do as We Do, Not as You Think: the Conformity of Large Language Models
97. ICLR 2025Enhancing Robust Fairness via Confusional Spectral Regularization
98. ICLR 2025Expected Sliced Transport Plans
99. ICLR 2025Exploring Local Memorization in Diffusion Models via Bright Ending Attention
100. ICLR 2025Fair Submodular Cover

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.