社会层面 · privacy论文趋势 2023–2026

主要结论

• 社会层面 · privacy论文从 2023 年的 21 篇增长到 2026 年的 138 篇，三年间扩大到约 6.6 倍。
• NeurIPS 是发社会层面 · privacy论文最多的会议，2023–2026 年共 215 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 · accountability transparency and interpretability：同时属于两个主题的论文从 2023 年的 0 篇增至 2026 年的 93 篇。
• 在「对齐与负责任 AI」的 5 个主题里，它的 2026 年论文数排第 4；同组增长最快的社会层面 · safety是 93 倍，社会层面 · privacy是 6.6 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 2026Assessing Per-Sample Membership Inference Vulnerability without Retraining
• ICML 2026Accuracy-First Rényi Differential Privacy and Post-Processing Immunity
• ICLR 2026Mitigating Privacy Risk via Forget Set-Free Unlearning
• CVPR 2026Protego User-Centric Pose-Invariant Privacy Protection Against Face Recognition-Induced Digital Footprint
• NeurIPS 2025A Generalized Binary Tree Mechanism for Private Approximation of All-Pair Shortest Distances
• ICML 2025Breaking the $n^{1.5}$ Additive Error Barrier for Private and Efficient Graph Sparsification via Private Expander Decomposition
• ICLR 2025Machine Unlearning via Simulated Oracle Matching
• CVPR 2025Enhancing Facial Privacy Protection via Weakening Diffusion Purification
• NeurIPS 2024Adaptive Randomized Smoothing: Certified Adversarial Robustness for Multi-Step Defences
• ICML 2024Privacy Preserving Adaptive Experiment Design
• ICLR 2024Beyond Memorization: Violating Privacy via Inference with Large Language Models
• CVPR 2024Validating Privacy-Preserving Face Recognition under a Minimum Assumption
• NeurIPS 2023Faster approximate subgraph counts with privacy
• ICML 2023GuardHFL: Privacy Guardian for Heterogeneous Federated Learning
• ICLR 2023Decepticons: Corrupted Transformers Breach Privacy in Federated Learning for Language Models
• CVPR 2023Privacy-Preserving Representations Are Not Enough: Recovering Scene Content From Camera Poses
• NeurIPS 2026Asymmetric Invertible Threat: Learning Reversible Privacy Defense for Face Recognition
• ICML 2026Accurate, Private, Secure, Federated U-statistics with Higher Degree
• ICLR 2026Measuring Physical-World Privacy Awareness of Large Language Models: An Evaluation Benchmark
• CVPR 2026LDP-Slicing Local Differential Privacy for Images via Randomized Bit-Plane Slicing

全部社会层面 · privacy论文

共 71 篇，第 1 / 2 页

1. ICML 2025A Certified Unlearning Approach without Access to Source Data
2. ICML 2025A Unified Theoretical Analysis of Private and Robust Offline Alignment: from RLHF to DPO
3. ICML 2025Adapting to Linear Separable Subsets with Large-Margin in Differentially Private Learning
4. ICML 2025An Efficient Private GPT Never Autoregressively Decodes
5. ICML 2025Approximate Differential Privacy of the $\ell_2$ Mechanism
6. ICML 2025Auditing $f$-differential privacy in one run
7. ICML 2025Auditing Prompt Caching in Language Model APIs
8. ICML 2025Breaking the $n^{1.5}$ Additive Error Barrier for Private and Efficient Graph Sparsification via Private Expander Decomposition
9. ICML 2025Breaking the Quadratic Barrier: Robust Cardinality Sketches for Adaptive Queries
10. ICML 2025CAN: Leveraging Clients As Navigators for Generative Replay in Federated Continual Learning
11. ICML 2025Cape: Context-Aware Prompt Perturbation Mechanism with Differential Privacy
12. ICML 2025Certification for Differentially Private Prediction in Gradient-Based Training
13. ICML 2025Certified Unlearning for Neural Networks
14. ICML 2025Clients Collaborate: Flexible Differentially Private Federated Learning with Guaranteed Improvement of Utility-Privacy Trade-off
15. ICML 2025Contrastive Private Data Synthesis via Weighted Multi-PLM Fusion
16. ICML 2025Differential Privacy Under Class Imbalance: Methods and Empirical Insights
17. ICML 2025Differentially Private Analysis for Binary Response Models: Optimality, Estimation, and Inference
18. ICML 2025Differentially Private Boxplots
19. ICML 2025Differentially Private Federated $k$-Means Clustering with Server-Side Data
20. ICML 2025Differentially Private Space-Efficient Algorithms for Counting Distinct Elements in the Turnstile Model
21. ICML 2025Distributed Differentially Private Data Analytics via Secure Sketching
22. ICML 2025DMM: Distributed Matrix Mechanism for Differentially-Private Federated Learning Based on Constant-Overhead Linear Secret Resharing
23. ICML 2025DRAG: Data Reconstruction Attack using Guided Diffusion
24. ICML 2025Editable Concept Bottleneck Models
25. ICML 2025Efficient Source-free Unlearning via Energy-Guided Data Synthesis and Discrimination-Aware Multitask Optimization
26. ICML 2025EgoPrivacy: What Your First-Person Camera Says About You?
27. ICML 2025Empirical Privacy Variance
28. ICML 2025EncryptedLLM: Privacy-Preserving Large Language Model Inference via GPU-Accelerated Fully Homomorphic Encryption
29. ICML 2025Fast Exact Unlearning for In-Context Learning Data for LLMs
30. ICML 2025Faster Rates for Private Adversarial Bandits
31. ICML 2025Federated Disentangled Tuning with Textual Prior Decoupling and Visual Dynamic Adaptation
32. ICML 2025FOCoOp: Enhancing Out-of-Distribution Robustness in Federated Prompt Learning for Vision-Language Models
33. ICML 2025GHOST: Generalizable One-Shot Federated Graph Learning with Proxy-Based Topology Knowledge Retention
34. ICML 2025Going Deeper into Locally Differentially Private Graph Neural Networks
35. ICML 2025Gradient Inversion of Multimodal Models
36. ICML 2025Improved Sample Complexity for Private Nonsmooth Nonconvex Optimization
37. ICML 2025It's My Data Too: Private ML for Datasets with Multi-User Training Examples
38. ICML 2025Janus: Dual-Server Multi-Round Secure Aggregation with Verifiability for Federated Learning
39. ICML 2025Kona: An Efficient Privacy-Preservation Framework for KNN Classification by Communication Optimization
40. ICML 2025Leveraging Model Guidance to Extract Training Data from Personalized Diffusion Models
41. ICML 2025Leveraging Per-Instance Privacy for Machine Unlearning
42. ICML 2025Leveraging Randomness in Model and Data Partitioning for Privacy Amplification
43. ICML 2025Lightweight Protocols for Distributed Private Quantile Estimation
44. ICML 2025Local Pan-privacy for Federated Analytics
45. ICML 2025Noisy SIGNSGD Is More Differentially Private Than You (Might) Think
46. ICML 2025On the Private Estimation of Smooth Transport Maps
47. ICML 2025Optimal Survey Design for Private Mean Estimation
48. ICML 2025Optimizing Noise Distributions for Differential Privacy
49. ICML 2025PASS: Private Attributes Protection with Stochastic Data Substitution
50. ICML 2025PCEvolve: Private Contrastive Evolution for Synthetic Dataset Generation via Few-Shot Private Data and Generative APIs

常见问题

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

共 431 篇，按年份分别是 2023 年 21 篇、2024 年 117 篇、2025 年 155 篇、2026 年 138 篇。

NeurIPS 2026 有多少篇社会层面 · privacy论文？

NeurIPS 2026 有 44 篇社会层面 · privacy论文，上一届是 80 篇。

ICLR 2026 有多少篇社会层面 · privacy论文？

ICLR 2026 有 2 篇社会层面 · privacy论文，上一届是 2 篇。

ICML 2026 有多少篇社会层面 · privacy论文？

ICML 2026 有 90 篇社会层面 · privacy论文，上一届是 71 篇。

CVPR 2026 有多少篇社会层面 · privacy论文？

CVPR 2026 有 2 篇社会层面 · privacy论文，上一届是 2 篇。

哪个会议的社会层面 · privacy论文最多？

NeurIPS，2023–2026 年共 215 篇。