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 368 篇,第 1 / 8 页
- CVPR 2026Decoupling Bias Aligning Distributions Synergistic Fairness Optimization for Deepfake Detection
- CVPR 2026EMMA Concept Erasure Benchmark with Comprehensive Semantic Metrics and Diverse
- CVPR 2026FairLLaVA Fairness-Aware Parameter-Efficient Fine-Tuning for Large Vision-Language Assistants
- CVPR 2026FedRAC Rolling Submodel Allocation for Collaborative Fairness in Federated Learning
- CVPR 2026From Failure to Feedback Group Revision Unlocks Hard Cases in
- CVPR 2026Group Editing Edit Multiple Images in One Go
- CVPR 2026Hyperbolic Relational Prompts for Intersectional Fairness in Medical VLMs
- CVPR 2026Interpretable Debiasing of Vision-Language Models for Social Fairness
- ICLR 2026A Fair Bayesian Inference through Matched Gibbs Posterior
- ICLR 2026All That Glitters Is Not Gold: Key-Secured 3D Secrets within 3D Gaussian Splatting
- ICLR 2026Automated Interpretability Metrics Do Not Distinguish Trained and Random Transformers
- ICLR 2026AWM: Accurate Weight-Matrix Fingerprint for Large Language Models
- ICLR 2026Benchmarking Bias Mitigation Toward Fairness Without Harm from Vision to LVLMs
- ICLR 2026Benchmarking Stochastic Approximation Algorithms for Fairness-Constrained Training of Deep Neural Networks
- ICLR 2026Beyond Match Maximization and Fairness: Retention-Optimized Two-Sided Matching
- ICLR 2026Beyond Prompt-Induced Lies: Investigating LLM Deception on Benign Prompts
- ICLR 2026Bias Similarity Measurement: A Black-Box Audit of Fairness Across LLMs
- ICLR 2026BiasBusters: Uncovering and Mitigating Tool Selection Bias in Large Language Models
- ICLR 2026CLASH: Evaluating Language Models on Judging High-Stakes Dilemmas from Multiple Perspectives
- ICLR 2026Doubly-Regressing Approach for Subgroup Fairness
- ICLR 2026EigenBench: A Comparative Behavioral Measure of Value Alignment
- ICLR 2026Enhanced Generative Model Evaluation with Clipped Density and Coverage
- ICLR 2026Fair Classification by Direct Intervention on Operating Characteristics
- ICLR 2026Fairness via Independence: A General Regularization Framework for Machine Learning
- ICLR 2026Fairness-Aware Multi-view Evidential Learning with Adaptive Prior
- ICLR 2026Fast and Stable Riemannian Metrics on SPD Manifolds via Cholesky Product Geometry
- ICLR 2026FERD: Fairness-Enhanced Data-Free Adversarial Robustness Distillation
- ICLR 2026GradShield: Alignment Preserving Finetuning
- ICLR 2026On Fairness of Task Arithmetic: The Role of Task Vectors
- ICLR 2026Optimal Transport-Induced Samples against Out-of-Distribution Overconfidence
- ICLR 2026Regulating Internal Evidence Flows for Robust Learning Under Spurious Correlations
- ICLR 2026Rethinking Pareto Frontier: On the Optimal Trade-offs in Fair Classification
- ICLR 2026Riemannian Zeroth-Order Gradient Estimation with Structure-Preserving Metrics for Geodesically Incomplete Manifolds
- ICLR 2026Spilled Energy in Large Language Models
- ICLR 2026WaterDrum: Watermark-based Data-centric Unlearning Metric
- ICML 2026Beyond Procedure: Substantive Fairness in Conformal Prediction
- ICML 2026Capacitated Fair-Range Clustering: Hardness and Approximation Algorithms
- ICML 2026Desirable Effort Fairness and Optimality Trade-offs in Strategic Learning
- ICML 2026Differentiable Optimization Layers for Guaranteed Fairness in Deep Learning
- ICML 2026Divide-and-Denoise: A Game-Theoretic Method for Fairly Composing Diffusion Models
- ICML 2026Fair Classification with Efficient and Post-hoc Controllable Fairness-Accuracy Trade-off
- ICML 2026Fair Dataset Distillation via Cross-Group Barycenter Alignment
- ICML 2026FairMerging: Rethinking Model Merging through the Lens of Fairness
- ICML 2026Fairness in Aggregation: Optimal Top-$k$ and Improved Full Ranking
- ICML 2026FairRARI: A Plug and Play Framework for Fairness-Aware PageRank
- ICML 2026Fine-to-Coarse Fairness-Informed Multi-View Clustering
- ICML 2026From Individual Calibration to Reliable Classifiers: ALD Parameterization with mPAIC Guarantees
- ICML 2026Incentivizing Truthfulness and Collaborative Fairness in Bayesian Learning
- ICML 2026MIRA: A Score for Conditional Distribution Accuracy and Model Comparison
- ICML 2026Optimal Transport under Group Fairness Constraints
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。