隐私攻击论文趋势 2023–2026

成员推断等

统计范围：NeurIPS、ICLR、ICML、CVPR 四个会议，2023–2026 年，共 698 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

隐私攻击论文数，按年份和会议
年份NeurIPSICLRICMLCVPR合计
202346242925124
202463534222180
202545832918175
2026551023824219

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

全部隐私攻击论文

年份全部2023202420252026
会议全部NeurIPSICLRICMLCVPR

共 209 篇，第 4 / 5 页

  1. NeurIPS 2024SPEAR: Exact Gradient Inversion of Batches in Federated Learning
  2. NeurIPS 2024Stealth edits to large language models
  3. NeurIPS 2024SuperDeepFool: a new fast and accurate minimal adversarial attack
  4. NeurIPS 2024TARP-VP: Towards Evaluation of Transferred Adversarial Robustness and Privacy on Label Mapping Visual Prompting Models
  5. NeurIPS 2024The Limits of Differential Privacy in Online Learning
  6. NeurIPS 2024Trap-MID: Trapdoor-based Defense against Model Inversion Attacks
  7. NeurIPS 2024Tree of Attacks: Jailbreaking Black-Box LLMs Automatically
  8. NeurIPS 2024Unelicitable Backdoors via Cryptographic Transformer Circuits
  9. NeurIPS 2024United We Stand, Divided We Fall: Fingerprinting Deep Neural Networks via Adversarial Trajectories
  10. NeurIPS 2024Watermarking Makes Language Models Radioactive
  11. NeurIPS 2024WaveAttack: Asymmetric Frequency Obfuscation-based Backdoor Attacks Against Deep Neural Networks
  12. NeurIPS 2024Wide Two-Layer Networks can Learn from Adversarial Perturbations
  13. NeurIPS 2024WildTeaming at Scale: From In-the-Wild Jailbreaks to (Adversarially) Safer Language Models
  14. NeurIPS 2023$k$-Means Clustering with Distance-Based Privacy
  15. NeurIPS 2023A Unified Detection Framework for Inference-Stage Backdoor Defenses
  16. NeurIPS 2023A Unified Fast Gradient Clipping Framework for DP-SGD
  17. NeurIPS 2023Adaptive Privacy Composition for Accuracy-first Mechanisms
  18. NeurIPS 2023Adversarially Robust Distributed Count Tracking via Partial Differential Privacy
  19. NeurIPS 2023Batchnorm Allows Unsupervised Radial Attacks
  20. NeurIPS 2023Blurred-Dilated Method for Adversarial Attacks
  21. NeurIPS 2023Bounding the Invertibility of Privacy-preserving Instance Encoding using Fisher Information
  22. NeurIPS 2023Bounding training data reconstruction in DP-SGD
  23. NeurIPS 2023Counting Distinct Elements in the Turnstile Model with Differential Privacy under Continual Observation
  24. NeurIPS 2023Counting Distinct Elements Under Person-Level Differential Privacy
  25. NeurIPS 2023Data Minimization at Inference Time
  26. NeurIPS 2023DiffAttack: Evasion Attacks Against Diffusion-Based Adversarial Purification
  27. NeurIPS 2023Differentially Private Statistical Inference through $\beta$-Divergence One Posterior Sampling
  28. NeurIPS 2023Do SSL Models Have Déjà Vu? A Case of Unintended Memorization in Self-supervised Learning
  29. NeurIPS 2023Faster approximate subgraph counts with privacy
  30. NeurIPS 2023FedGame: A Game-Theoretic Defense against Backdoor Attacks in Federated Learning
  31. NeurIPS 2023Flocks of Stochastic Parrots: Differentially Private Prompt Learning for Large Language Models
  32. NeurIPS 2023GAN You See Me? Enhanced Data Reconstruction Attacks against Split Inference
  33. NeurIPS 2023Gaussian Differential Privacy on Riemannian Manifolds
  34. NeurIPS 2023Gaussian Membership Inference Privacy
  35. NeurIPS 2023Hidden Poison: Machine Unlearning Enables Camouflaged Poisoning Attacks
  36. NeurIPS 2023k-Median Clustering via Metric Embedding: Towards Better Initialization with Differential Privacy
  37. NeurIPS 2023Label Robust and Differentially Private Linear Regression: Computational and Statistical Efficiency
  38. NeurIPS 2023Label-Only Model Inversion Attacks via Knowledge Transfer
  39. NeurIPS 2023LinGCN: Structural Linearized Graph Convolutional Network for Homomorphically Encrypted Inference
  40. NeurIPS 2023Marich: A Query-efficient Distributionally Equivalent Model Extraction Attack
  41. NeurIPS 2023Minimax Risks and Optimal Procedures for Estimation under Functional Local Differential Privacy
  42. NeurIPS 2023On Computing Pairwise Statistics with Local Differential Privacy
  43. NeurIPS 2023On Private and Robust Bandits
  44. NeurIPS 2023Optimal Unbiased Randomizers for Regression with Label Differential Privacy
  45. NeurIPS 2023Posthoc privacy guarantees for collaborative inference with modified Propose-Test-Release
  46. NeurIPS 2023Practical Differentially Private Hyperparameter Tuning with Subsampling
  47. NeurIPS 2023Privacy Amplification via Compression: Achieving the Optimal Privacy-Accuracy-Communication Trade-off in Distributed Mean Estimation
  48. NeurIPS 2023Privacy Assessment on Reconstructed Images: Are Existing Evaluation Metrics Faithful to Human Perception?
  49. NeurIPS 2023Privacy Auditing with One (1) Training Run
  50. NeurIPS 2023Private Federated Frequency Estimation: Adapting to the Hardness of the Instance

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 查隐私攻击在 ICLR 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": "privacy-attacks"}

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常见问题

2023–2026 年四大会议一共有多少篇隐私攻击论文？
共 698 篇，按年份分别是 2023 年 124 篇、2024 年 180 篇、2025 年 175 篇、2026 年 219 篇。
NeurIPS 2026 有多少篇隐私攻击论文？
NeurIPS 2026 有 55 篇隐私攻击论文，上一届是 45 篇。
ICLR 2026 有多少篇隐私攻击论文？
ICLR 2026 有 102 篇隐私攻击论文，上一届是 83 篇。
ICML 2026 有多少篇隐私攻击论文？
ICML 2026 有 38 篇隐私攻击论文，上一届是 29 篇。
CVPR 2026 有多少篇隐私攻击论文？
CVPR 2026 有 24 篇隐私攻击论文，上一届是 18 篇。
哪个会议的隐私攻击论文最多？
ICLR，2023–2026 年共 262 篇。

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