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 5 of 8

201. ICLR 2024LCOT: Linear Circular Optimal Transport
202. ICLR 2024Learning to Reject Meets Long-tail Learning
203. ICLR 2024Like Oil and Water: Group Robustness Methods and Poisoning Defenses May Be at Odds
204. ICLR 2024Near-Optimal Solutions of Constrained Learning Problems
205. ICLR 2024On the Fairness ROAD: Robust Optimization for Adversarial Debiasing
206. ICLR 2024Perceptual Scales Predicted by Fisher Information Metrics
207. ICLR 2024Post-hoc bias scoring is optimal for fair classification
208. ICLR 2024Procedural Fairness Through Decoupling Objectionable Data Generating Components
209. ICLR 2024Structural Fairness-aware Active Learning for Graph Neural Networks
210. ICLR 2024Time Fairness in Online Knapsack Problems
211. ICLR 2024Towards Best Practices of Activation Patching in Language Models: Metrics and Methods
212. ICLR 2024Towards Poisoning Fair Representations
213. ICML 2024A General Online Algorithm for Optimizing Complex Performance Metrics
214. ICML 2024Adapting Static Fairness to Sequential Decision-Making: Bias Mitigation Strategies towards Equal Long-term Benefit Rate
215. ICML 2024Benchmarking Deletion Metrics with the Principled Explanations
216. ICML 2024Centralized Selection with Preferences in the Presence of Biases
217. ICML 2024Differentially Private Worst-group Risk Minimization
218. ICML 2024Discovering Symmetry Breaking in Physical Systems with Relaxed Group Convolution
219. ICML 2024Disparate Impact on Group Accuracy of Linearization for Private Inference
220. ICML 2024Equilibrium of Data Markets with Externality
221. ICML 2024Evaluating Model Bias Requires Characterizing its Mistakes
222. ICML 2024Fair Risk Control: A Generalized Framework for Calibrating Multi-group Fairness Risks
223. ICML 2024FairProof : Confidential and Certifiable Fairness for Neural Networks
224. ICML 2024FRAPPÉ: A Group Fairness Framework for Post-Processing Everything
225. ICML 2024Grokking Group Multiplication with Cosets
226. ICML 2024Hierarchical Integral Probability Metrics: A distance on random probability measures with low sample complexity
227. ICML 2024How Far Can Fairness Constraints Help Recover From Biased Data?
228. ICML 2024Improving Group Robustness on Spurious Correlation Requires Preciser Group Inference
229. ICML 2024Individual Fairness in Graph Decomposition
230. ICML 2024Monotone Individual Fairness
231. ICML 2024On The Fairness Impacts of Hardware Selection in Machine Learning
232. ICML 2024On the Maximal Local Disparity of Fairness-Aware Classifiers
233. ICML 2024PairNet: Training with Observed Pairs to Estimate Individual Treatment Effect
234. ICML 2024Position: Scarce Resource Allocations That Rely On Machine Learning Should Be Randomized
235. ICML 2024Promoting External and Internal Equities Under Ex-Ante/Ex-Post Metrics in Online Resource Allocation
236. ICML 2024Remembering to Be Fair: Non-Markovian Fairness in Sequential Decision Making
237. ICML 2024Size-invariance Matters: Rethinking Metrics and Losses for Imbalanced Multi-object Salient Object Detection
238. ICML 2024Stability and Multigroup Fairness in Ranking with Uncertain Predictions
239. ICML 2024Standardized Interpretable Fairness Measures for Continuous Risk Scores
240. ICML 2024Variational Partial Group Convolutions for Input-Aware Partial Equivariance of Rotations and Color-Shifts
241. NeurIPS 2024ABCFair: an Adaptable Benchmark approach for Comparing Fairness Methods
242. NeurIPS 2024Achievable Fairness on Your Data With Utility Guarantees
243. NeurIPS 2024Bisimulation Metrics are Optimal Transport Distances, and Can be Computed Efficiently
244. NeurIPS 2024Counterfactual Fairness by Combining Factual and Counterfactual Predictions
245. NeurIPS 2024CultureLLM: Incorporating Cultural Differences into Large Language Models
246. NeurIPS 2024Do Counterfactually Fair Image Classifiers Satisfy Group Fairness? -- A Theoretical and Empirical Study
247. NeurIPS 2024Does Egalitarian Fairness Lead to Instability? The Fairness Bounds in Stable Federated Learning Under Altruistic Behaviors
248. NeurIPS 2024Enhancing Robustness of Last Layer Two-Stage Fair Model Corrections
249. NeurIPS 2024Enriching Disentanglement: From Logical Definitions to Quantitative Metrics
250. NeurIPS 2024Fair Bilevel Neural Network (FairBiNN): On Balancing fairness and accuracy via Stackelberg Equilibrium

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.