公平指标论文趋势 2023–2026
群体/个体公平
统计范围:NeurIPS、ICLR、ICML、CVPR 四个会议,2023–2026 年,共 368 篇被归入该主题的论文。
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。
各会议论文数
按年份和会议统计
| 年份 | NeurIPS | ICLR | ICML | CVPR | 合计 |
|---|---|---|---|---|---|
| 2023 | 28 | 22 | 26 | 2 | 78 |
| 2024 | 50 | 30 | 28 | 10 | 118 |
| 2025 | 33 | 30 | 24 | 7 | 94 |
| 2026 | 26 | 27 | 17 | 8 | 78 |
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 1 / 3 页
- CVPR 2024Classes Are Not Equal: An Empirical Study on Image Recognition Fairness
- CVPR 2024FairCLIP: Harnessing Fairness in Vision-Language Learning
- CVPR 2024FairDeDup: Detecting and Mitigating Vision-Language Fairness Disparities in Semantic Dataset Deduplication
- CVPR 2024GARField: Group Anything with Radiance Fields
- CVPR 2024Identifying Important Group of Pixels using Interactions
- CVPR 2024Learning Group Activity Features Through Person Attribute Prediction
- CVPR 2024Neural Lineage
- CVPR 2024Preserving Fairness Generalization in Deepfake Detection
- CVPR 2024Towards Fairness-Aware Adversarial Learning
- CVPR 2024Utility-Fairness Trade-Offs and How to Find Them
- ICLR 2024Adversarial Attacks on Fairness of Graph Neural Networks
- ICLR 2024Aligning Relational Learning with Lipschitz Fairness
- ICLR 2024Assessing Uncertainty in Similarity Scoring: Performance & Fairness in Face Recognition
- ICLR 2024Balancing Act: Constraining Disparate Impact in Sparse Models
- ICLR 2024Causal Fairness under Unobserved Confounding: A Neural Sensitivity Framework
- ICLR 2024Consistent algorithms for multi-label classification with macro-at-$k$ metrics
- ICLR 2024Debiasing Attention Mechanism in Transformer without Demographics
- ICLR 2024Deceptive Fairness Attacks on Graphs via Meta Learning
- ICLR 2024Demystifying Local & Global Fairness Trade-offs in Federated Learning Using Partial Information Decomposition
- ICLR 2024Enhancing Group Fairness in Online Settings Using Oblique Decision Forests
- ICLR 2024Estimating Shape Distances on Neural Representations with Limited Samples
- ICLR 2024Fair and Efficient Contribution Valuation for Vertical Federated Learning
- ICLR 2024Fair Classifiers that Abstain without Harm
- ICLR 2024fairret: a Framework for Differentiable Fairness Regularization Terms
- ICLR 2024FairSeg: A Large-Scale Medical Image Segmentation Dataset for Fairness Learning Using Segment Anything Model with Fair Error-Bound Scaling
- ICLR 2024FairTune: Optimizing Parameter Efficient Fine Tuning for Fairness in Medical Image Analysis
- ICLR 2024FFB: A Fair Fairness Benchmark for In-Processing Group Fairness Methods
- ICLR 2024Language Model Detectors Are Easily Optimized Against
- ICLR 2024LCOT: Linear Circular Optimal Transport
- ICLR 2024Learning to Reject Meets Long-tail Learning
- ICLR 2024Like Oil and Water: Group Robustness Methods and Poisoning Defenses May Be at Odds
- ICLR 2024Near-Optimal Solutions of Constrained Learning Problems
- ICLR 2024On the Fairness ROAD: Robust Optimization for Adversarial Debiasing
- ICLR 2024Perceptual Scales Predicted by Fisher Information Metrics
- ICLR 2024Post-hoc bias scoring is optimal for fair classification
- ICLR 2024Procedural Fairness Through Decoupling Objectionable Data Generating Components
- ICLR 2024Structural Fairness-aware Active Learning for Graph Neural Networks
- ICLR 2024Time Fairness in Online Knapsack Problems
- ICLR 2024Towards Best Practices of Activation Patching in Language Models: Metrics and Methods
- ICLR 2024Towards Poisoning Fair Representations
- ICML 2024A General Online Algorithm for Optimizing Complex Performance Metrics
- ICML 2024Adapting Static Fairness to Sequential Decision-Making: Bias Mitigation Strategies towards Equal Long-term Benefit Rate
- ICML 2024Benchmarking Deletion Metrics with the Principled Explanations
- ICML 2024Centralized Selection with Preferences in the Presence of Biases
- ICML 2024Differentially Private Worst-group Risk Minimization
- ICML 2024Discovering Symmetry Breaking in Physical Systems with Relaxed Group Convolution
- ICML 2024Disparate Impact on Group Accuracy of Linearization for Private Inference
- ICML 2024Equilibrium of Data Markets with Externality
- ICML 2024Evaluating Model Bias Requires Characterizing its Mistakes
- ICML 2024Fair Risk Control: A Generalized Framework for Calibrating Multi-group Fairness Risks
在 Claude、Cursor 里直接问这个趋势
接上 Paperlist MCP 后,写综述、挑方向或准备投稿时,不用离开对话框就能拿到这页的数字:每年各会议的论文数、增长倍数、涨得最快的子方向和代表论文,AI 会按你的问题整理。
可以直接复制这句话问 AI
用 paperlist 查公平指标在 NeurIPS 2023–2026 的论文趋势,哪一年涨得最快?
AI 会调用的工具:get_topic_stats {"topic": "fairness-metrics"}
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。