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 1 / 8 页

1. CVPR 2026Decoupling Bias Aligning Distributions Synergistic Fairness Optimization for Deepfake Detection
2. CVPR 2026FedRAC Rolling Submodel Allocation for Collaborative Fairness in Federated Learning
3. CVPR 2026Interpretable Debiasing of Vision-Language Models for Social Fairness
4. CVPR 2026Omni-MMSI Toward Identity-attributed Social Interaction Understanding
5. ICLR 2026Bi-Criteria Metric Distortion
6. ICLR 2026Bi-directional Bias Attribution: Debiasing Large Language Models without Modifying Prompts
7. ICLR 2026Culture in Action: Evaluating Text-to-Image Models through Social Activities
8. ICLR 2026FERD: Fairness-Enhanced Data-Free Adversarial Robustness Distillation
9. ICML 2026A Game-Theoretic Framework for Measuring and Explaining Metric Compatibility in Fair Machine Learning
10. ICML 2026Adaptive Generation of Bias-Eliciting Questions for LLMs
11. ICML 2026Ambiguous Strategic Classification
12. ICML 2026Anchored Decoding: Provably Reducing Copyright Risk for Any Language Model
13. ICML 2026Belief Dynamics Reveal the Dual Nature of In-Context Learning and Activation Steering
14. ICML 2026Beyond Additive Decompositions: Interpretability Through Separability
15. ICML 2026Beyond Procedure: Substantive Fairness in Conformal Prediction
16. ICML 2026COFT: Counterfactual–Conformal Decoding for Fair Chain‑of‑Thought Reasoning in Large Language Models
17. ICML 2026COPF: An Online Framework for Deployment-Stable Counterfactual Fairness in Evolving Graphs
18. ICML 2026Demystifying the Optimal Fair Classifier in Multi-Class Classification
19. ICML 2026Density-Aware Translation of Spurious Correlations in Zero-Shot VLMs
20. ICML 2026Differentiable Optimization Layers for Guaranteed Fairness in Deep Learning
21. ICML 2026Enhancing Conformal Prediction via Class Similarity
22. ICML 2026Equalized Generative Treatment: Matching f-divergences for Fairness in Generative Models
23. ICML 2026Exactly Computing do-Shapley Values
24. ICML 2026Extending Fair Null-Space Projections for Continuous Attributes to Kernel Methods
25. ICML 2026Fair Classification with Efficient and Post-hoc Controllable Fairness-Accuracy Trade-off
26. ICML 2026Fair Dataset Distillation via Cross-Group Barycenter Alignment
27. ICML 2026Fair Decisions from Calibrated Scores: Achieving Optimal Classification While Satisfying Sufficiency
28. ICML 2026Fair Transit Stop Placement: A Clustering Perspective and Beyond
29. ICML 2026FairGB: A Fair Granular-Ball Generation Method for Data Classification
30. ICML 2026FairMerging: Rethinking Model Merging through the Lens of Fairness
31. ICML 2026Fairness in Aggregation: Optimal Top-$k$ and Improved Full Ranking
32. ICML 2026FairRARI: A Plug and Play Framework for Fairness-Aware PageRank
33. ICML 2026FairSSL: Fair Multimodal Self-Supervised Learning
34. ICML 2026FedEBA+: Towards Fair and Effective Federated Learning via Entropy-Based Model
35. ICML 2026Finding Most Influential Sets
36. ICML 2026Graph-Preference Learning: Debiasing Network-Sampled Human Feedback for Target Welfare Estimation
37. ICML 2026HoloFair: Unified T2I Fairness Evaluation and Fair-GRPO Debiasing
38. ICML 2026Hugging Carbon: Quantifying the Training Carbon Emissions of AI Models at Scale
39. ICML 2026IACW: Intent-Aware Controllable Watermarking for Scalable Authorial Intent Attribution
40. ICML 2026Improved Algorithms for Nash Welfare in Linear Bandits
41. ICML 2026Incentivizing Truthfulness and Collaborative Fairness in Bayesian Learning
42. ICML 2026Is Data Shapley Not Better than Random in Data Selection? Ask NASH
43. ICML 2026Knowing Bias, Doing Better: Mitigating Social Bias in LLMs via Know-Bias Neuron Enhancement
44. ICML 2026Language Bias in LVLMs: From In-Depth Analysis to Simple and Effective Mitigation
45. ICML 2026Large Language Models Develop Novel Social Biases Through Adaptive Exploration
46. ICML 2026Locate then Correct: Debiasing Attention Heads in CLIP
47. ICML 2026Long-term Fairness with Selective Labels
48. ICML 2026MAFE: Enabling Equitable Algorithm Design in Multi-Agent Multi-Stage Decision-Making Systems
49. ICML 2026Maximin Relative Improvement: Fair Learning as a Bargaining Problem
50. ICML 2026OC-space: a Unifying Perspective on Verification of Tree Ensembles

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。