社会层面 · fairness论文趋势 2023–2026
AI 社会议题:fairness
统计范围:NeurIPS、ICLR、ICML、CVPR 四个会议,2023–2026 年,共 358 篇被归入该主题的论文。
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。
各会议论文数
按年份和会议统计
| 年份 | NeurIPS | ICLR | ICML | CVPR | 合计 |
|---|---|---|---|---|---|
| 2023 | 19 | 8 | 7 | 2 | 36 |
| 2024 | 56 | 9 | 11 | 3 | 79 |
| 2025 | 62 | 8 | 61 | 1 | 132 |
| 2026 | 43 | 4 | 60 | 4 | 111 |
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 60 篇,第 1 / 2 页
- ICML 2026A Game-Theoretic Framework for Measuring and Explaining Metric Compatibility in Fair Machine Learning
- ICML 2026Adaptive Generation of Bias-Eliciting Questions for LLMs
- ICML 2026Ambiguous Strategic Classification
- ICML 2026Anchored Decoding: Provably Reducing Copyright Risk for Any Language Model
- ICML 2026Belief Dynamics Reveal the Dual Nature of In-Context Learning and Activation Steering
- ICML 2026Beyond Additive Decompositions: Interpretability Through Separability
- ICML 2026Beyond Procedure: Substantive Fairness in Conformal Prediction
- ICML 2026COFT: Counterfactual–Conformal Decoding for Fair Chain‑of‑Thought Reasoning in Large Language Models
- ICML 2026COPF: An Online Framework for Deployment-Stable Counterfactual Fairness in Evolving Graphs
- ICML 2026Demystifying the Optimal Fair Classifier in Multi-Class Classification
- ICML 2026Density-Aware Translation of Spurious Correlations in Zero-Shot VLMs
- ICML 2026Differentiable Optimization Layers for Guaranteed Fairness in Deep Learning
- ICML 2026Enhancing Conformal Prediction via Class Similarity
- ICML 2026Equalized Generative Treatment: Matching f-divergences for Fairness in Generative Models
- ICML 2026Exactly Computing do-Shapley Values
- ICML 2026Extending Fair Null-Space Projections for Continuous Attributes to Kernel Methods
- ICML 2026Fair Classification with Efficient and Post-hoc Controllable Fairness-Accuracy Trade-off
- ICML 2026Fair Dataset Distillation via Cross-Group Barycenter Alignment
- ICML 2026Fair Decisions from Calibrated Scores: Achieving Optimal Classification While Satisfying Sufficiency
- ICML 2026Fair Transit Stop Placement: A Clustering Perspective and Beyond
- ICML 2026FairGB: A Fair Granular-Ball Generation Method for Data Classification
- 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 2026FairSSL: Fair Multimodal Self-Supervised Learning
- ICML 2026FedEBA+: Towards Fair and Effective Federated Learning via Entropy-Based Model
- ICML 2026Finding Most Influential Sets
- ICML 2026Graph-Preference Learning: Debiasing Network-Sampled Human Feedback for Target Welfare Estimation
- ICML 2026HoloFair: Unified T2I Fairness Evaluation and Fair-GRPO Debiasing
- ICML 2026Hugging Carbon: Quantifying the Training Carbon Emissions of AI Models at Scale
- ICML 2026IACW: Intent-Aware Controllable Watermarking for Scalable Authorial Intent Attribution
- ICML 2026Improved Algorithms for Nash Welfare in Linear Bandits
- ICML 2026Incentivizing Truthfulness and Collaborative Fairness in Bayesian Learning
- ICML 2026Is Data Shapley Not Better than Random in Data Selection? Ask NASH
- ICML 2026Knowing Bias, Doing Better: Mitigating Social Bias in LLMs via Know-Bias Neuron Enhancement
- ICML 2026Language Bias in LVLMs: From In-Depth Analysis to Simple and Effective Mitigation
- ICML 2026Large Language Models Develop Novel Social Biases Through Adaptive Exploration
- ICML 2026Locate then Correct: Debiasing Attention Heads in CLIP
- ICML 2026Long-term Fairness with Selective Labels
- ICML 2026MAFE: Enabling Equitable Algorithm Design in Multi-Agent Multi-Stage Decision-Making Systems
- ICML 2026Maximin Relative Improvement: Fair Learning as a Bargaining Problem
- ICML 2026OC-space: a Unifying Perspective on Verification of Tree Ensembles
- ICML 2026Old Habits Die Hard: How Conversational History Geometrically Traps LLMs
- ICML 2026Online Social Welfare Function-based Resource Allocation
- ICML 2026Optimal Fair Aggregation of Crowdsourced Noisy Labels using Demographic Parity Constraints
- ICML 2026Optimal Regularization for Performative Learning
- ICML 2026Optimal Transport Group Counterfactual Explanations
- ICML 2026Optimal Transport under Group Fairness Constraints
- ICML 2026Pluralistic Leaderboards
- ICML 2026Prompt Injection as Role Confusion
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 查社会层面 · fairness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": "social-fairness"}
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。