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

137 papers, page 1 of 3

1. NeurIPS 2026A Comprehensive View of Fairness through Distributional Stability
2. NeurIPS 2026Adversarial Group Fairness in Contextual Bandits: When Robust is Not Fair
3. NeurIPS 2026Auditing Cross-Lingual Fairness in Language Model Watermarking
4. NeurIPS 2026Beyond Proxy Metrics: MLLM-Based Human Surrogate Evaluation for Explainable AI
5. NeurIPS 2026Cost Efficient Fairness Audit Under Partial Feedback
6. NeurIPS 2026Data-Free Metrics Are Not Invariant Under Functionality-Preserving Reparametrisations
7. NeurIPS 2026Faithfulness Metrics Don't Measure Faithfulness: A Meta-Evaluation with Ground Truth
8. NeurIPS 2026Forecasting Downstream Performance of LLMs With Proxy Metrics
9. NeurIPS 2026FRInGe: Distribution-Space Integrated Gradients with Fisher–Rao Geometry
10. NeurIPS 2026Geometry-Aware Similarity Metrics for Neural Representations on Riemannian and Statistical Manifolds
11. NeurIPS 2026How Does Pruning Change Decisions in Large Language Models?
12. NeurIPS 2026Inferring learning rules in deep neural network architectures from animal learning data
13. NeurIPS 2026Malicious Node Injection: A Transferable Adversarial Attack on GNN Fairness
14. NeurIPS 2026Matrix-Free Natural Gradient via Stochastic Truncated Metrics
15. NeurIPS 2026Overcoming the Resolution Limit: Significance-Aware Regularization for Intersectional Fairness
16. NeurIPS 2026Post-Processing Guarantees for Classification under Linear-Fractional Performance Metrics
17. NeurIPS 2026Practical Estimation of the Bayes Optimal Fairness-Accuracy Tradeoff with Soft Labels
18. NeurIPS 2026Recovering Clean Evaluation Metrics from Contaminated Benchmarks
19. NeurIPS 2026Reviewer Scores Are Not Comparable Across Research Areas in ML Peer Review
20. NeurIPS 2026Scalable Fair Learning via Cramér-von Mises Regularization
21. NeurIPS 2026Simultaneous Individual, Group and Multigroup Fairness in Set Covering Problems
22. NeurIPS 2026Space Group Conditional Flow Matching
23. NeurIPS 2026Spectral-Spatial Interpretation
24. NeurIPS 2026Stay Fair! Ensuring Group Fairness in Diffusion Models Across Guidance Scales
25. NeurIPS 2026Strategic Causal Policy Learning: Welfare, Safety, and Fairness Thresholds
26. NeurIPS 2026The Pok\'emon Theorem and other Fairness Impossibility Results
27. NeurIPS 2025Analyzing Similarity Metrics for Data Selection for Language Model Pretraining
28. NeurIPS 2025Are Pixel-Wise Metrics Reliable for Computerized Tomography Reconstruction?
29. NeurIPS 2025Bridging Arbitrary and Tree Metrics via Differentiable Gromov Hyperbolicity
30. NeurIPS 2025Coresets for Clustering Under Stochastic Noise
31. NeurIPS 2025Do Automatic Factuality Metrics Measure Factuality? A Critical Evaluation
32. NeurIPS 2025Fair Continuous Resource Allocation with Equality of Impact
33. NeurIPS 2025Fair Matroid Selection
34. NeurIPS 2025Fair Minimum Labeling: Efficient Temporal Network Activations for Reachability and Equity
35. NeurIPS 2025Fairness under Competition
36. NeurIPS 2025Fairness-aware Anomaly Detection via Fair Projection
37. NeurIPS 2025Fairness-aware Bayes Optimal Functional Classification
38. NeurIPS 2025Fairness-Regularized Online Optimization with Switching Costs
39. NeurIPS 2025FedFACT: A Provable Framework for Controllable Group-Fairness Calibration in Federated Learning
40. NeurIPS 2025Follow the Energy, Find the Path: Riemannian Metrics from Energy-Based Models
41. NeurIPS 2025Improved Algorithms for Fair Matroid Submodular Maximization
42. NeurIPS 2025Individual Fairness In Strategic Classification
43. NeurIPS 2025Individually Fair Diversity Maximization
44. NeurIPS 2025Integral Imprecise Probability Metrics
45. NeurIPS 2025Kernel-based Equalized Odds: A Quantification of Accuracy-Fairness Trade-off in Fair Representation Learning
46. NeurIPS 2025MLIP Arena: Advancing Fairness and Transparency in Machine Learning Interatomic Potentials via an Open, Accessible Benchmark Platform
47. NeurIPS 2025On Group Sufficiency Under Label Bias
48. NeurIPS 2025On Hierarchies of Fairness Notions in Cake Cutting: From Proportionality to Super Envy-Freeness
49. NeurIPS 2025On Optimal Steering to Achieve Exact Fairness
50. NeurIPS 2025On the VC dimension of deep group convolutional neural networks

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.