社会层面 · fairness论文趋势 2023–2026

主要结论

• 社会层面 · fairness论文从 2023 年的 36 篇增长到 2026 年的 111 篇，三年间扩大到约 3.1 倍。
• NeurIPS 是发社会层面 · fairness论文最多的会议，2023–2026 年共 180 篇，占四个会议总量的 50%。
• 交叉方向里涨得最快的是社会层面 · safety：同时属于两个主题的论文从 2023 年的 1 篇增至 2026 年的 56 篇。
• 在「对齐与负责任 AI」的 5 个主题里，它的 2026 年论文数排第 5；同组增长最快的社会层面 · safety是 93 倍，社会层面 · fairness是 3.1 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 2026Beyond Feature Disruption: Boundary-Diverting Unlearnable Examples against Linear Probing
• ICML 2026A Game-Theoretic Framework for Measuring and Explaining Metric Compatibility in Fair Machine Learning
• ICLR 2026Bi-directional Bias Attribution: Debiasing Large Language Models without Modifying Prompts
• CVPR 2026Omni-MMSI Toward Identity-attributed Social Interaction Understanding
• NeurIPS 2025Discretization-free Multicalibration through Loss Minimization over Tree Ensembles
• ICML 2025Dissecting Submission Limit in Desk-Rejections: A Mathematical Analysis of Fairness in AI Conference Policies
• ICLR 2025Prompting Fairness: Integrating Causality to Debias Large Language Models
• CVPR 2025Revisiting Fairness in Multitask Learning: A Performance-Driven Approach for Variance Reduction
• NeurIPS 2024A Closer Look at AUROC and AUPRC under Class Imbalance
• ICML 2024Position: Scarce Resource Allocations That Rely On Machine Learning Should Be Randomized
• ICLR 2024Procedural Fairness Through Decoupling Objectionable Data Generating Components
• CVPR 2024Preserving Fairness Generalization in Deepfake Detection
• NeurIPS 2023[Re] Fairness Guarantees under Demographic Shift
• ICML 2023Fairness in Streaming Submodular Maximization over a Matroid Constraint
• ICLR 2023Fairness-aware Contrastive Learning with Partially Annotated Sensitive Attributes
• CVPR 2023Improving Fairness in Facial Albedo Estimation via Visual-Textual Cues
• NeurIPS 2026Chatter Attack: Resource Consumption Attack for Large Language Models
• ICML 2026Adaptive Generation of Bias-Eliciting Questions for LLMs
• ICLR 2026Bi-Criteria Metric Distortion
• CVPR 2026Decoupling Bias Aligning Distributions Synergistic Fairness Optimization for Deepfake Detection

全部社会层面 · fairness论文

共 358 篇，第 3 / 8 页

101. NeurIPS 2026Practical Estimation of the Bayes Optimal Fairness-Accuracy Tradeoff with Soft Labels
102. NeurIPS 2026PrivateSeal: Low-Sensitivity Latent Directions for Diffusion-Resilient User-Specific Watermarking
103. NeurIPS 2026Provable Explanations for Any-Order Neural Additive Models
104. NeurIPS 2026Sample Transform Cost-Based Training-Free Hallucination Detector for Large Language Models
105. NeurIPS 2026Stay Fair! Ensuring Group Fairness in Diffusion Models Across Guidance Scales
106. NeurIPS 2026TensorCommitments: A Lightweight Verifiable Inference for Large Language Models
107. NeurIPS 2026The Algorithm Is Not the Behavior: Learned Priors Override Look-Ahead in a Chess-Playing Neural Network
108. NeurIPS 2026The Geometric Inductive Bias of Grokking: Bypassing Phase Transitions via Architectural Topology
109. NeurIPS 2026The Panel Complexity of Sortition: Is 12 Angry Men Enough?
110. NeurIPS 2026Towards Fair Graph Generation Without Sensitive Attribute
111. NeurIPS 2026Training ML Models with Predictable Failures
112. CVPR 2025Revisiting Fairness in Multitask Learning: A Performance-Driven Approach for Variance Reduction
113. ICLR 2025A Generic Framework for Conformal Fairness
114. ICLR 2025An Effective Theory of Bias Amplification
115. ICLR 2025CEB: Compositional Evaluation Benchmark for Fairness in Large Language Models
116. ICLR 2025Collapsed Language Models Promote Fairness
117. ICLR 2025Competitive Fair Scheduling with Predictions
118. ICLR 2025Prompting Fairness: Integrating Causality to Debias Large Language Models
119. ICLR 2025Rethinking Fair Representation Learning for Performance-Sensitive Tasks
120. ICLR 2025Towards Marginal Fairness Sliced Wasserstein Barycenter
121. ICML 2025"Who experiences large model decay and why?" A Hierarchical Framework for Diagnosing Heterogeneous Performance Drift
122. ICML 2025(How) Can Transformers Predict Pseudo-Random Numbers?
123. ICML 2025Accelerating Spectral Clustering under Fairness Constraints
124. ICML 2025Automatically Interpreting Millions of Features in Large Language Models
125. ICML 2025B-score: Detecting biases in large language models using response history
126. ICML 2025Causal Logistic Bandits with Counterfactual Fairness Constraints
127. ICML 2025Confidential Guardian: Cryptographically Prohibiting the Abuse of Model Abstention
128. ICML 2025Correlated Errors in Large Language Models
129. ICML 2025DANCE: Dual Unbiased Expansion with Group-acquired Alignment for Out-of-distribution Graph Fairness Learning
130. ICML 2025Detecting Strategic Deception with Linear Probes
131. ICML 2025Discovering Spoofing Attempts on Language Model Watermarks
132. ICML 2025Disparate Conditional Prediction in Multiclass Classifiers
133. ICML 2025Dissecting Submission Limit in Desk-Rejections: A Mathematical Analysis of Fairness in AI Conference Policies
134. ICML 2025Explaining, Fast and Slow: Abstraction and Refinement of Provable Explanations
135. ICML 2025ExpProof : Operationalizing Explanations for Confidential Models with ZKPs
136. ICML 2025Extractive Structures Learned in Pretraining Enable Generalization on Finetuned Facts
137. ICML 2025FACTER: Fairness-Aware Conformal Thresholding and Prompt Engineering for Enabling Fair LLM-Based Recommender Systems
138. ICML 2025Fair Clustering via Alignment
139. ICML 2025FairICP: Encouraging Equalized Odds via Inverse Conditional Permutation
140. ICML 2025Fairness on Principal Stratum: A New Perspective on Counterfactual Fairness
141. ICML 2025Fairness Overfitting in Machine Learning: An Information-Theoretic Perspective
142. ICML 2025Fast Estimation of Partial Dependence Functions using Trees
143. ICML 2025FDGen: A Fairness-Aware Graph Generation Model
144. ICML 2025From Individual Experience to Collective Evidence: A Reporting-Based Framework for Identifying Systemic Harms
145. ICML 2025Generative Social Choice: The Next Generation
146. ICML 2025Graph Inverse Style Transfer for Counterfactual Explainability
147. ICML 2025Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs
148. ICML 2025Kandinsky Conformal Prediction: Beyond Class- and Covariate-Conditional Coverage
149. ICML 2025KGMark: A Diffusion Watermark for Knowledge Graphs
150. ICML 2025Learning Classifiers That Induce Markets

常见问题

2023–2026 年四大会议一共有多少篇社会层面 · fairness论文？

共 358 篇，按年份分别是 2023 年 36 篇、2024 年 79 篇、2025 年 132 篇、2026 年 111 篇。

NeurIPS 2026 有多少篇社会层面 · fairness论文？

NeurIPS 2026 有 43 篇社会层面 · fairness论文，上一届是 62 篇。

ICLR 2026 有多少篇社会层面 · fairness论文？

ICLR 2026 有 4 篇社会层面 · fairness论文，上一届是 8 篇。

ICML 2026 有多少篇社会层面 · fairness论文？

ICML 2026 有 60 篇社会层面 · fairness论文，上一届是 61 篇。

CVPR 2026 有多少篇社会层面 · fairness论文？

CVPR 2026 有 4 篇社会层面 · fairness论文，上一届是 1 篇。

哪个会议的社会层面 · fairness论文最多？

NeurIPS，2023–2026 年共 180 篇。