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 62 篇，第 1 / 2 页

1. NeurIPS 2025A Unified Framework for Fair Graph Generation: Theoretical Guarantees and Empirical Advances
2. NeurIPS 2025Additive Models Explained: A Computational Complexity Approach
3. NeurIPS 2025Adjacent Words, Divergent Intents: Jailbreaking Large Language Models via Task Concurrency
4. NeurIPS 2025Boosting the Uniqueness of Neural Networks Fingerprints with Informative Triggers
5. NeurIPS 2025Causally Reliable Concept Bottleneck Models
6. NeurIPS 2025Correcting misinterpretations of additive models
7. NeurIPS 2025Detoxifying Large Language Models via Autoregressive Reward Guided Representation Editing
8. NeurIPS 2025Discovering Opinion Intervals from Conflicts in Signed Graphs
9. NeurIPS 2025Discretization-free Multicalibration through Loss Minimization over Tree Ensembles
10. NeurIPS 2025Distributive Fairness in Large Language Models: Evaluating Alignment with Human Values
11. NeurIPS 2025Does Representation Guarantee Welfare?
12. NeurIPS 2025DPA: A one-stop metric to measure bias amplification in classification datasets
13. NeurIPS 2025Efficient Fairness-Performance Pareto Front Computation
14. NeurIPS 2025Fair Continuous Resource Allocation with Equality of Impact
15. NeurIPS 2025Fair Deepfake Detectors Can Generalize
16. NeurIPS 2025Fair Matroid Selection
17. NeurIPS 2025Fair Representation Learning with Controllable High Confidence Guarantees via Adversarial Inference
18. NeurIPS 2025FairDICE: Fairness-Driven Offline Multi-Objective Reinforcement Learning
19. NeurIPS 2025Fairness under Competition
20. NeurIPS 2025Fairness-aware Anomaly Detection via Fair Projection
21. NeurIPS 2025Fairness-aware Bayes Optimal Functional Classification
22. NeurIPS 2025FairNet: Dynamic Fairness Correction without Performance Loss via Contrastive Conditional LoRA
23. NeurIPS 2025Faithful Group Shapley Value
24. NeurIPS 2025FedFACT: A Provable Framework for Controllable Group-Fairness Calibration in Federated Learning
25. NeurIPS 2025From Specificity to Generality: Revisiting Generalizable Artifacts in Detecting Face Deepfakes
26. NeurIPS 2025Geometric Imbalance in Semi-Supervised Node Classification
27. NeurIPS 2025Guiding LLM Decision-Making with Fairness Reward Models
28. NeurIPS 2025Homogeneous Algorithms Can Reduce Competition in Personalized Pricing
29. NeurIPS 2025Incentivizing Time-Aware Fairness in Data Sharing
30. NeurIPS 2025Individual Fairness In Strategic Classification
31. NeurIPS 2025Individually Fair Diversity Maximization
32. NeurIPS 2025Kernel-based Equalized Odds: A Quantification of Accuracy-Fairness Trade-off in Fair Representation Learning
33. NeurIPS 2025Minimizing False-Positive Attributions in Explanations of Non-Linear Models
34. NeurIPS 2025Monoculture or Multiplicity: Which Is It?
35. NeurIPS 2025Noise Injection Reveals Hidden Capabilities of Sandbagging Language Models
36. NeurIPS 2025On Fairness of Unified Multimodal Large Language Model for Image Generation
37. NeurIPS 2025On Group Sufficiency Under Label Bias
38. NeurIPS 2025On Hierarchies of Fairness Notions in Cake Cutting: From Proportionality to Super Envy-Freeness
39. NeurIPS 2025On Optimal Steering to Achieve Exact Fairness
40. NeurIPS 2025Path-specific effects for pulse-oximetry guided decisions in critical care
41. NeurIPS 2025Performative Validity of Recourse Explanations
42. NeurIPS 2025Predicting the Performance of Black-box Language Models with Follow-up Queries
43. NeurIPS 2025Provable Gradient Editing of Deep Neural Networks
44. NeurIPS 2025Representational Difference Explanations
45. NeurIPS 2025RespoDiff: Dual-Module Bottleneck Transformation for Responsible & Faithful T2I Generation
46. NeurIPS 2025Rethinking Fair Federated Learning from Parameter and Client View
47. NeurIPS 2025Scalable Fingerprinting of Large Language Models
48. NeurIPS 2025Secure and Confidential Certificates of Online Fairness
49. NeurIPS 2025Selective Omniprediction and Fair Abstention
50. NeurIPS 2025Semantic Representation Attack against Aligned Large Language Models

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。