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 6 of 8

251. NeurIPS 2024Fair GLASSO: Estimating Fair Graphical Models with Unbiased Statistical Behavior
252. NeurIPS 2024Fair Kernel K-Means: from Single Kernel to Multiple Kernel
253. NeurIPS 2024Fair Online Bilateral Trade
254. NeurIPS 2024Fair Secretaries with Unfair Predictions
255. NeurIPS 2024Fair Wasserstein Coresets
256. NeurIPS 2024Fairness and Efficiency in Online Class Matching
257. NeurIPS 2024Fairness in Social Influence Maximization via Optimal Transport
258. NeurIPS 2024Fairness without Harm: An Influence-Guided Active Sampling Approach
259. NeurIPS 2024Fairness-Aware Estimation of Graphical Models
260. NeurIPS 2024Fairness-Aware Meta-Learning via Nash Bargaining
261. NeurIPS 2024Graph-based Uncertainty Metrics for Long-form Language Model Generations
262. NeurIPS 2024Improving Adversarial Robust Fairness via Anti-Bias Soft Label Distillation
263. NeurIPS 2024Improving Subgroup Robustness via Data Selection
264. NeurIPS 2024Interpolating Item and User Fairness in Multi-Sided Recommendations
265. NeurIPS 2024Learning to Understand: Identifying Interactions via the Möbius Transform
266. NeurIPS 2024MAGNET: Improving the Multilingual Fairness of Language Models with Adaptive Gradient-Based Tokenization
267. NeurIPS 2024Mind the Graph When Balancing Data for Fairness or Robustness
268. NeurIPS 2024Mitigating Spurious Correlations via Disagreement Probability
269. NeurIPS 2024Monomial Matrix Group Equivariant Neural Functional Networks
270. NeurIPS 2024Multi-Group Proportional Representation in Retrieval
271. NeurIPS 2024Navigating the Maze of Explainable AI: A Systematic Approach to Evaluating Methods and Metrics
272. NeurIPS 2024OxonFair: A Flexible Toolkit for Algorithmic Fairness
273. NeurIPS 2024Parameterized Approximation Schemes for Fair-Range Clustering
274. NeurIPS 2024Perceptual Fairness in Image Restoration
275. NeurIPS 2024Promoting Fairness Among Dynamic Agents in Online-Matching Markets under Known Stationary Arrival Distributions
276. NeurIPS 2024Proportional Fairness in Non-Centroid Clustering
277. NeurIPS 2024Quantitative Convergences of Lie Group Momentum Optimizers
278. NeurIPS 2024Reproducibility study of "Robust Fair Clustering: A Novel Fairness Attack and Defense Framework"
279. NeurIPS 2024Reproducibility Study of "Robust Fair Clustering: A Novel Fairness Attack and Defense Framework"
280. NeurIPS 2024Reproducibility Study: Equal Improvability: A New Fairness Notion Considering the Long-Term Impact
281. NeurIPS 2024Statistical Inference for Fairness Auditing
282. NeurIPS 2024The Fairness-Quality Tradeoff in Clustering
283. NeurIPS 2024The Fragility of Fairness: Causal Sensitivity Analysis for Fair Machine Learning
284. NeurIPS 2024Theoretical and Empirical Insights into the Origins of Degree Bias in Graph Neural Networks
285. NeurIPS 2024Towards Explainable Evaluation Metrics for Machine Translation
286. NeurIPS 2024Towards Harmless Rawlsian Fairness Regardless of Demographic Prior
287. NeurIPS 2024Towards Heterogeneous Long-tailed Learning: Benchmarking, Metrics, and Toolbox
288. NeurIPS 2024User-item fairness tradeoffs in recommendations
289. NeurIPS 2024Wasserstein Distributionally Robust Optimization through the Lens of Structural Causal Models and Individual Fairness
290. NeurIPS 2024When is Multicalibration Post-Processing Necessary?
291. CVPR 2023Improving Fairness in Facial Albedo Estimation via Visual-Textual Cues
292. CVPR 2023Music-Driven Group Choreography
293. ICLR 2023Bias Propagation in Federated Learning
294. ICLR 2023Bitrate-Constrained DRO: Beyond Worst Case Robustness To Unknown Group Shifts
295. ICLR 2023Confidential-PROFITT: Confidential PROof of FaIr Training of Trees
296. ICLR 2023Equal Improvability: A New Fairness Notion Considering the Long-term Impact
297. ICLR 2023FaiREE: fair classification with finite-sample and distribution-free guarantee
298. ICLR 2023FairGBM: Gradient Boosting with Fairness Constraints
299. ICLR 2023Fairness and Accuracy under Domain Generalization
300. ICLR 2023Fairness-aware Contrastive Learning with Partially Annotated Sensitive Attributes

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.