社会层面 · privacy论文趋势 2023–2026

AI 社会议题：privacy

统计范围：NeurIPS、ICLR、ICML、CVPR 四个会议，2023–2026 年，共 431 篇被归入该主题的论文。

主要结论

每年论文数

各会议论文数

按年份和会议统计

社会层面 · privacy论文数，按年份和会议
年份NeurIPSICLRICMLCVPR合计
2023457521
20248711136117
2025802712155
2026442902138

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

全部社会层面 · privacy论文

年份全部2023202420252026
会议全部NeurIPSICLRICMLCVPR

共 215 篇，第 1 / 5 页

  1. NeurIPS 2026A Private Empirical Defense Against Privacy Audits
  2. NeurIPS 2026Assessing Per-Sample Membership Inference Vulnerability without Retraining
  3. NeurIPS 2026Asymmetric Invertible Threat: Learning Reversible Privacy Defense for Face Recognition
  4. NeurIPS 2026Asymptotically Optimal Best Arm Identification with Fixed-Budget under Differential Privacy
  5. NeurIPS 2026Auditing Privacy Leakage in Tabular Foundation Model Embeddings
  6. NeurIPS 2026BEAGLE: Behavior-Enforced Agent for Grounded Learner Emulation
  7. NeurIPS 2026Benchmarking Membership Privacy Risks in Preference-Based LLM Post-Training
  8. NeurIPS 2026Causal Evaluation of Membership Inference Attacks
  9. NeurIPS 2026Detecting Hidden ML Training With Zero-Overhead Telemetry
  10. NeurIPS 2026DP-EGGROLL: Centered Fitness-Vector Privatization for Backprop-Free Differentially Private Optimization
  11. NeurIPS 2026DPrivBench: Benchmarking LLMs' Reasoning for Differential Privacy
  12. NeurIPS 2026Efficient Label Distribution Inference Attack and Defense on Classifier Weights in Federated Learning
  13. NeurIPS 2026ERIS: Enhancing Privacy and Scalability in Federated Learning via Federated Shard Aggregation
  14. NeurIPS 2026𝑓-Differential Privacy Filters: Validity and Approximate Solutions
  15. NeurIPS 2026Federated Concept-Based Models: Interpretable models with distributed supervision
  16. NeurIPS 2026FILOsofer: A TEE-Shielded Model Partitioning Framework based on Fisher Information-Guided LoRA Obfuscation
  17. NeurIPS 2026GOLIATH: Gradient Inversion of Tabular Diffusion Models
  18. NeurIPS 2026How Far Are VLMs from Privacy Awareness in the Physical World? An Empirical Study
  19. NeurIPS 2026Jaguar: Fast Private CNN Inference with Power-of-Two Homomorphic Arithmetic
  20. NeurIPS 2026Learning the Signature of Memorization in Autoregressive Language Models
  21. NeurIPS 2026Leveraging Soft Prompts for Privacy Attacks in Federated Prompt Tuning
  22. NeurIPS 2026Lumberjack: Better Differentially Private Random Forests through Heavy Hitter Detection in Trees
  23. NeurIPS 2026Mitigating Memorization Where It Happens
  24. NeurIPS 2026Models Designed to Forget: Machine Unlearning via Key Deletion
  25. NeurIPS 2026MPCI-Bench: A Benchmark for Multimodal Pairwise Contextual Integrity Privacy Evaluation of Language Model Agents
  26. NeurIPS 2026On Differentially Private Mechanisms for Linear Regression
  27. NeurIPS 2026On Inherent Privacy of Posterior Sampling: A Unified R\'enyi-Divergence Framework
  28. NeurIPS 2026Online Differentially Private Consistent Clustering
  29. NeurIPS 2026Optimal Algorithms for Fixed-Graph Multi-Attribution Privacy
  30. NeurIPS 2026Optimal Rates for Adaptive Private $k$-PCA
  31. NeurIPS 2026Optimal Rates for Differentially Private Hypothesis Testing with E-values
  32. NeurIPS 2026PACZero: PAC-Private Fine-Tuning of Language Models via Sign Quantization
  33. NeurIPS 2026Position: Life-Logging Video Streams Make the Privacy–Utility Trade-off Inevitable
  34. NeurIPS 2026Privacy Amplification Persists under Unlimited Synthetic Data Release
  35. NeurIPS 2026Privacy by Postprocessing the Discrete Laplace Mechanism
  36. NeurIPS 2026Privacy Meets Hierarchy: Differentially Private Distributed Trilevel Learning
  37. NeurIPS 2026Privacy Risk Scales with Effective Dimension in Federated Learning
  38. NeurIPS 2026PrivacySIM: Evaluating LLM Simulation of User Privacy Behavior
  39. NeurIPS 2026Private Online Prediction from Experts with Small Losses
  40. NeurIPS 2026Sampling-Free Privacy Accounting for Matrix Mechanisms under Random Allocation
  41. NeurIPS 2026Sequential Membership Inference Attacks
  42. NeurIPS 2026Sort, Partition, Randomize: Optimal Binary Hypothesis Testing under Local Differential Privacy
  43. NeurIPS 2026The BatchNorm Illusion: Diagnosing Normalization Artifacts in Machine Unlearning Evaluation
  44. NeurIPS 2026Understanding Private Evolution as Learning-Augmented Clustering
  45. NeurIPS 2025A Generalized Binary Tree Mechanism for Private Approximation of All-Pair Shortest Distances
  46. NeurIPS 2025A Private Approximation of the 2nd-Moment Matrix of Any Subsamplable Input
  47. NeurIPS 2025A Reliable Cryptographic Framework for Empirical Machine Unlearning Evaluation
  48. NeurIPS 2025Adaptive Data Analysis for Growing Data
  49. NeurIPS 2025Adaptive Sigmoid Clipping for Balancing the Direction–Magnitude Mismatch Trade-off in Differentially Private Learning
  50. NeurIPS 2025AgentDAM: Privacy Leakage Evaluation for Autonomous Web Agents

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 · privacy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-privacy"}

两分钟接入 Paperlist MCP（Claude Code、Cursor、Codex、ChatGPT）

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。

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