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 2 / 8 页

51. ICML 2026Old Habits Die Hard: How Conversational History Geometrically Traps LLMs
52. ICML 2026Online Social Welfare Function-based Resource Allocation
53. ICML 2026Optimal Fair Aggregation of Crowdsourced Noisy Labels using Demographic Parity Constraints
54. ICML 2026Optimal Regularization for Performative Learning
55. ICML 2026Optimal Transport Group Counterfactual Explanations
56. ICML 2026Optimal Transport under Group Fairness Constraints
57. ICML 2026Pluralistic Leaderboards
58. ICML 2026Prompt Injection as Role Confusion
59. ICML 2026RECAST: Model Reconstruction via Counterfactual-Aware Wasserstein Geometry under Limited Data
60. ICML 2026SAEs-BrainMap: Unveiling the Emergence of Specialized Concepts in Deep Models via Brain Alignment
61. ICML 2026Self-correcting for Debiasing Large Language Models
62. ICML 2026Test-Time Debiasing with Probabilistic Prompts via Wasserstein Distance in Vision-Language Models
63. ICML 2026Three Years of r/ChatGPT: Societal Impact Evaluations from Social Media Data
64. ICML 2026Towards Steering without Sacrifice: Principled Training of Steering Vectors for Prompt-only Interventions
65. ICML 2026Unlearning Isn't Deletion: Investigating Reversibility of Machine Unlearning in LLMs
66. ICML 2026What is Missing? Explaining Neurons Activated by Absent Concepts
67. ICML 2026When Random Saliency Looks Trained: Architectural Center Bias in CNN Interpretability
68. ICML 2026Who Evaluates AI's Social Impacts? Mapping Coverage and Gaps in First and Third Party Evaluations
69. NeurIPS 2026A Comprehensive View of Fairness through Distributional Stability
70. NeurIPS 2026Adversarial Group Fairness in Contextual Bandits: When Robust is Not Fair
71. NeurIPS 2026AI-Mediated Communication Can Steer Collective Opinion
72. NeurIPS 2026Auditing Cross-Lingual Fairness in Language Model Watermarking
73. NeurIPS 2026Beyond Confidence: Rethinking Self-Assessments for Performance Prediction in LLMs
74. NeurIPS 2026Beyond Feature Disruption: Boundary-Diverting Unlearnable Examples against Linear Probing
75. NeurIPS 2026Black-Box Inference of LLM Architectural Properties with Restrictive API Access
76. NeurIPS 2026CalArena: A Large Scale Post-Hoc Calibration Benchmark
77. NeurIPS 2026Chatter Attack: Resource Consumption Attack for Large Language Models
78. NeurIPS 2026Cognitive bias benchmarks should incorporate insights from ecological rationality
79. NeurIPS 2026Compact Representations of Impact-Based Fair-Ranking Policies
80. NeurIPS 2026Compressing Collections of Trees with Decision Equivalence
81. NeurIPS 2026Conceal, Reconstruct, Jailbreak: Exploiting the Reconstruction--Concealment Tradeoff in MLLMs
82. NeurIPS 2026Cost Efficient Fairness Audit Under Partial Feedback
83. NeurIPS 2026Embeddings for Preferences, Not Semantics
84. NeurIPS 2026Escape the Context Manifold: Preventing DiT In-Context Editing via Conditional Flow Hijacking
85. NeurIPS 2026Finding Interpretable Prompt-Specific Circuits in Language Models
86. NeurIPS 2026Gradient-Mine Units: Scorched-Earth Strategy for Model Protection against Unauthorized Fine-Tuning
87. NeurIPS 2026Hierarchical Conformal Classification
88. NeurIPS 2026How Hard is it to Rig a Benchmark? A Social Choice Analysis of Leaderboard Robustness
89. NeurIPS 2026How Likely Are Voting Rules Equitable?
90. NeurIPS 2026Integral Probability Boundaries
91. NeurIPS 2026Intersectional Fairness via Mixed-Integer Optimization
92. NeurIPS 2026Jointly Robust Fairness: Overcoming Simultaneous Label and Attribute Noise
93. NeurIPS 2026LLM Rheology: Auditing Refusal Geometry in Aligned Language Models
94. NeurIPS 2026Localizing Input Uncertainty Quantification for Large Language Models via Shapley Values
95. NeurIPS 2026Malicious Node Injection: A Transferable Adversarial Attack on GNN Fairness
96. NeurIPS 2026Metaphor Is Not All Attention Needs
97. NeurIPS 2026Nash Social Welfare for Multi Armed Bandits: Trajectory-wise Expected and High Probability Regret
98. NeurIPS 2026On the Burden of Achieving Fairness in Conformal Prediction
99. NeurIPS 2026Overcoming the Resolution Limit: Significance-Aware Regularization for Intersectional Fairness
100. NeurIPS 2026Persona-Model Collapse in Emergent Misalignment

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。