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 4 of 8

151. NeurIPS 2025Fairness-Regularized Online Optimization with Switching Costs
152. NeurIPS 2025FedFACT: A Provable Framework for Controllable Group-Fairness Calibration in Federated Learning
153. NeurIPS 2025Follow the Energy, Find the Path: Riemannian Metrics from Energy-Based Models
154. NeurIPS 2025Improved Algorithms for Fair Matroid Submodular Maximization
155. NeurIPS 2025Individual Fairness In Strategic Classification
156. NeurIPS 2025Individually Fair Diversity Maximization
157. NeurIPS 2025Integral Imprecise Probability Metrics
158. NeurIPS 2025Kernel-based Equalized Odds: A Quantification of Accuracy-Fairness Trade-off in Fair Representation Learning
159. NeurIPS 2025MLIP Arena: Advancing Fairness and Transparency in Machine Learning Interatomic Potentials via an Open, Accessible Benchmark Platform
160. NeurIPS 2025On Group Sufficiency Under Label Bias
161. NeurIPS 2025On Hierarchies of Fairness Notions in Cake Cutting: From Proportionality to Super Envy-Freeness
162. NeurIPS 2025On Optimal Steering to Achieve Exact Fairness
163. NeurIPS 2025On the VC dimension of deep group convolutional neural networks
164. NeurIPS 2025Online Multi-Class Selection with Group Fairness Guarantee
165. NeurIPS 2025OpenUnlearning: Accelerating LLM Unlearning via Unified Benchmarking of Methods and Metrics
166. NeurIPS 2025Size-adaptive Hypothesis Testing for Fairness
167. NeurIPS 2025Some Optimizers are More Equal: Understanding the Role of Optimizers in Group Fairness
168. NeurIPS 2025Space Group Equivariant Crystal Diffusion
169. NeurIPS 2025Statistical Parity with Exponential Weights
170. NeurIPS 2025The Price of Opportunity Fairness in Matroid Allocation Problems
171. NeurIPS 2025Unifying Proportional Fairness in Centroid and Non-Centroid Clustering
172. NeurIPS 2025When majority rules, minority loses: bias amplification of gradient descent
173. CVPR 2024Classes Are Not Equal: An Empirical Study on Image Recognition Fairness
174. CVPR 2024FairCLIP: Harnessing Fairness in Vision-Language Learning
175. CVPR 2024FairDeDup: Detecting and Mitigating Vision-Language Fairness Disparities in Semantic Dataset Deduplication
176. CVPR 2024GARField: Group Anything with Radiance Fields
177. CVPR 2024Identifying Important Group of Pixels using Interactions
178. CVPR 2024Learning Group Activity Features Through Person Attribute Prediction
179. CVPR 2024Neural Lineage
180. CVPR 2024Preserving Fairness Generalization in Deepfake Detection
181. CVPR 2024Towards Fairness-Aware Adversarial Learning
182. CVPR 2024Utility-Fairness Trade-Offs and How to Find Them
183. ICLR 2024Adversarial Attacks on Fairness of Graph Neural Networks
184. ICLR 2024Aligning Relational Learning with Lipschitz Fairness
185. ICLR 2024Assessing Uncertainty in Similarity Scoring: Performance & Fairness in Face Recognition
186. ICLR 2024Balancing Act: Constraining Disparate Impact in Sparse Models
187. ICLR 2024Causal Fairness under Unobserved Confounding: A Neural Sensitivity Framework
188. ICLR 2024Consistent algorithms for multi-label classification with macro-at-$k$ metrics
189. ICLR 2024Debiasing Attention Mechanism in Transformer without Demographics
190. ICLR 2024Deceptive Fairness Attacks on Graphs via Meta Learning
191. ICLR 2024Demystifying Local & Global Fairness Trade-offs in Federated Learning Using Partial Information Decomposition
192. ICLR 2024Enhancing Group Fairness in Online Settings Using Oblique Decision Forests
193. ICLR 2024Estimating Shape Distances on Neural Representations with Limited Samples
194. ICLR 2024Fair and Efficient Contribution Valuation for Vertical Federated Learning
195. ICLR 2024Fair Classifiers that Abstain without Harm
196. ICLR 2024fairret: a Framework for Differentiable Fairness Regularization Terms
197. ICLR 2024FairSeg: A Large-Scale Medical Image Segmentation Dataset for Fairness Learning Using Segment Anything Model with Fair Error-Bound Scaling
198. ICLR 2024FairTune: Optimizing Parameter Efficient Fine Tuning for Fairness in Medical Image Analysis
199. ICLR 2024FFB: A Fair Fairness Benchmark for In-Processing Group Fairness Methods
200. ICLR 2024Language Model Detectors Are Easily Optimized Against

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.