公平指标论文趋势 2023–2026

主要结论

• 公平指标论文从 2023 年的 78 篇增长到 2026 年的 78 篇，三年间扩大到约 1.0 倍。
• NeurIPS 是发公平指标论文最多的会议，2023–2026 年共 137 篇，占四个会议总量的 37%。
• 交叉方向里涨得最快的是对齐与安全：同时属于两个主题的论文从 2023 年的 3 篇增至 2026 年的 18 篇。
• 在「因果与公平」的 5 个主题里，它的 2026 年论文数排第 3；同组增长最快的因果发现是 2.4 倍，公平指标是 1.0 倍。

代表论文

按年份和会议均匀挑选，方便快速看到每一届的样貌

• 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

全部公平指标论文

共 118 篇，第 2 / 3 页

51. ICML 2024FairProof : Confidential and Certifiable Fairness for Neural Networks
52. ICML 2024FRAPPÉ: A Group Fairness Framework for Post-Processing Everything
53. ICML 2024Grokking Group Multiplication with Cosets
54. ICML 2024Hierarchical Integral Probability Metrics: A distance on random probability measures with low sample complexity
55. ICML 2024How Far Can Fairness Constraints Help Recover From Biased Data?
56. ICML 2024Improving Group Robustness on Spurious Correlation Requires Preciser Group Inference
57. ICML 2024Individual Fairness in Graph Decomposition
58. ICML 2024Monotone Individual Fairness
59. ICML 2024On The Fairness Impacts of Hardware Selection in Machine Learning
60. ICML 2024On the Maximal Local Disparity of Fairness-Aware Classifiers
61. ICML 2024PairNet: Training with Observed Pairs to Estimate Individual Treatment Effect
62. ICML 2024Position: Scarce Resource Allocations That Rely On Machine Learning Should Be Randomized
63. ICML 2024Promoting External and Internal Equities Under Ex-Ante/Ex-Post Metrics in Online Resource Allocation
64. ICML 2024Remembering to Be Fair: Non-Markovian Fairness in Sequential Decision Making
65. ICML 2024Size-invariance Matters: Rethinking Metrics and Losses for Imbalanced Multi-object Salient Object Detection
66. ICML 2024Stability and Multigroup Fairness in Ranking with Uncertain Predictions
67. ICML 2024Standardized Interpretable Fairness Measures for Continuous Risk Scores
68. ICML 2024Variational Partial Group Convolutions for Input-Aware Partial Equivariance of Rotations and Color-Shifts
69. NeurIPS 2024ABCFair: an Adaptable Benchmark approach for Comparing Fairness Methods
70. NeurIPS 2024Achievable Fairness on Your Data With Utility Guarantees
71. NeurIPS 2024Bisimulation Metrics are Optimal Transport Distances, and Can be Computed Efficiently
72. NeurIPS 2024Counterfactual Fairness by Combining Factual and Counterfactual Predictions
73. NeurIPS 2024CultureLLM: Incorporating Cultural Differences into Large Language Models
74. NeurIPS 2024Do Counterfactually Fair Image Classifiers Satisfy Group Fairness? -- A Theoretical and Empirical Study
75. NeurIPS 2024Does Egalitarian Fairness Lead to Instability? The Fairness Bounds in Stable Federated Learning Under Altruistic Behaviors
76. NeurIPS 2024Enhancing Robustness of Last Layer Two-Stage Fair Model Corrections
77. NeurIPS 2024Enriching Disentanglement: From Logical Definitions to Quantitative Metrics
78. NeurIPS 2024Fair Bilevel Neural Network (FairBiNN): On Balancing fairness and accuracy via Stackelberg Equilibrium
79. NeurIPS 2024Fair GLASSO: Estimating Fair Graphical Models with Unbiased Statistical Behavior
80. NeurIPS 2024Fair Kernel K-Means: from Single Kernel to Multiple Kernel
81. NeurIPS 2024Fair Online Bilateral Trade
82. NeurIPS 2024Fair Secretaries with Unfair Predictions
83. NeurIPS 2024Fair Wasserstein Coresets
84. NeurIPS 2024Fairness and Efficiency in Online Class Matching
85. NeurIPS 2024Fairness in Social Influence Maximization via Optimal Transport
86. NeurIPS 2024Fairness without Harm: An Influence-Guided Active Sampling Approach
87. NeurIPS 2024Fairness-Aware Estimation of Graphical Models
88. NeurIPS 2024Fairness-Aware Meta-Learning via Nash Bargaining
89. NeurIPS 2024Graph-based Uncertainty Metrics for Long-form Language Model Generations
90. NeurIPS 2024Improving Adversarial Robust Fairness via Anti-Bias Soft Label Distillation
91. NeurIPS 2024Improving Subgroup Robustness via Data Selection
92. NeurIPS 2024Interpolating Item and User Fairness in Multi-Sided Recommendations
93. NeurIPS 2024Learning to Understand: Identifying Interactions via the Möbius Transform
94. NeurIPS 2024MAGNET: Improving the Multilingual Fairness of Language Models with Adaptive Gradient-Based Tokenization
95. NeurIPS 2024Mind the Graph When Balancing Data for Fairness or Robustness
96. NeurIPS 2024Mitigating Spurious Correlations via Disagreement Probability
97. NeurIPS 2024Monomial Matrix Group Equivariant Neural Functional Networks
98. NeurIPS 2024Multi-Group Proportional Representation in Retrieval
99. NeurIPS 2024Navigating the Maze of Explainable AI: A Systematic Approach to Evaluating Methods and Metrics
100. NeurIPS 2024OxonFair: A Flexible Toolkit for Algorithmic Fairness

常见问题

2023–2026 年四大会议一共有多少篇公平指标论文？

共 368 篇，按年份分别是 2023 年 78 篇、2024 年 118 篇、2025 年 94 篇、2026 年 78 篇。

NeurIPS 2026 有多少篇公平指标论文？

NeurIPS 2026 有 26 篇公平指标论文，上一届是 33 篇。

ICLR 2026 有多少篇公平指标论文？

ICLR 2026 有 27 篇公平指标论文，上一届是 30 篇。

ICML 2026 有多少篇公平指标论文？

ICML 2026 有 17 篇公平指标论文，上一届是 24 篇。

CVPR 2026 有多少篇公平指标论文？

CVPR 2026 有 8 篇公平指标论文，上一届是 7 篇。

哪个会议的公平指标论文最多？

NeurIPS，2023–2026 年共 137 篇。