Differential Privacy papers, 2023–2026

Key findings

• Differential Privacy fell from 117 papers in 2023 to 103 in 2026, so interest is cooling.
• NeurIPS publishes the most Differential Privacy work: 217 papers from 2023 to 2026, 45% of the four-venue total.
• The fastest-growing overlap is with Social aspects · accountability transparency and interpretability: papers tagged with both rose from 0 in 2023 to 22 in 2026.
• Among the 5 topics under Federated and Privacy, it ranks #3 by 2026 paper count; the fastest grower in the group, Secure Aggregation, is up 1.8x versus 0.9x here.

Representative papers

Spread across years and venues so every edition shows up

• NeurIPS 2026A Unified Framework for Adversary-Aware Differential Privacy Bounds
• ICML 2026Optimal conversion from Rényi Differential Privacy to $f$-Differential Privacy
• ICLR 2026Benchmarking Empirical Privacy Protection for Adaptations of Large Language Models
• CVPR 2026Fully Decentralized Certified Unlearning
• NeurIPS 2025Continual Release Moment Estimation with Differential Privacy
• ICML 2025Leveraging Per-Instance Privacy for Machine Unlearning
• ICLR 2025Data-adaptive Differentially Private Prompt Synthesis for In-Context Learning
• CVPR 2025Focal Split: Untethered Snapshot Depth from Differential Defocus
• NeurIPS 2024$\texttt{pfl-research}$: simulation framework for accelerating research in Private Federated Learning
• ICML 2024Delving into Differentially Private Transformer
• ICLR 2024Decoupled Marked Temporal Point Process using Neural Ordinary Differential Equations
• CVPR 2024Affine Equivariant Networks Based on Differential Invariants
• NeurIPS 2023(Amplified) Banded Matrix Factorization: A unified approach to private training
• ICML 2023Bayesian Estimation of Differential Privacy
• ICLR 2023A Statistical Framework for Personalized Federated Learning and Estimation: Theory, Algorithms, and Privacy
• CVPR 2023Learning To Generate Image Embeddings With User-Level Differential Privacy
• NeurIPS 2026Asymptotically Optimal Best Arm Identification with Fixed-Budget under Differential Privacy
• ICML 2026Optimization, Generalization and Differential Privacy Bounds for Gradient Descent on Kolmogorov–Arnold Networks
• ICLR 2026Beyond Membership: Limitations of Add/Remove Adjacency in Differential Privacy
• CVPR 2026LDP-Slicing Local Differential Privacy for Images via Randomized Bit-Plane Slicing

All Differential Privacy papers

146 papers, page 1 of 3

1. CVPR 2025Accurate Differential Operators for Hybrid Neural Fields
2. CVPR 2025Explicit Depth-Aware Blurry Video Frame Interpolation Guided by Differential Curves
3. CVPR 2025Focal Split: Untethered Snapshot Depth from Differential Defocus
4. CVPR 2025Unveiling Differences in Generative Models: A Scalable Differential Clustering Approach
5. ICLR 2025Adaptive Batch Size for Privately Finding Second-Order Stationary Points
6. ICLR 2025Adaptive Pruning of Pretrained Transformer via Differential Inclusions
7. ICLR 2025Convergent Privacy Loss of Noisy-SGD without Convexity and Smoothness
8. ICLR 2025Data-adaptive Differentially Private Prompt Synthesis for In-Context Learning
9. ICLR 2025Differential Transformer
10. ICLR 2025Differentially Private Federated Learning with Time-Adaptive Privacy Spending
11. ICLR 2025Differentially private learners for heterogeneous treatment effects
12. ICLR 2025Differentially private optimization for non-decomposable objective functions
13. ICLR 2025Differentially Private Steering for Large Language Model Alignment
14. ICLR 2025DiSK: Differentially Private Optimizer with Simplified Kalman Filter for Noise Reduction
15. ICLR 2025Enhancing Learning with Label Differential Privacy by Vector Approximation
16. ICLR 2025Gaussian Differentially Private Human Faces Under a Face Radial Curve Representation
17. ICLR 2025Learning from End User Data with Shuffled Differential Privacy over Kernel Densities
18. ICLR 2025Learning vector fields of differential equations on manifolds with geometrically constrained operator-valued kernels
19. ICLR 2025Local convergence of simultaneous min-max algorithms to differential equilibrium on Riemannian manifold
20. ICLR 2025Near-Exact Privacy Amplification for Matrix Mechanisms
21. ICLR 2025On the Price of Differential Privacy for Hierarchical Clustering
22. ICLR 2025Optimality of Matrix Mechanism on $\ell_p^p$-metric
23. ICLR 2025PFGuard: A Generative Framework with Privacy and Fairness Safeguards
24. ICLR 2025Privacy Auditing of Large Language Models
25. ICLR 2025Privacy-Preserving Personalized Federated Prompt Learning for Multimodal Large Language Models
26. ICLR 2025Private Mechanism Design via Quantile Estimation
27. ICLR 2025Privately Counting Partially Ordered Data
28. ICLR 2025Scaling up the Banded Matrix Factorization Mechanism for Large Scale Differentially Private ML
29. ICLR 2025Singular Subspace Perturbation Bounds via Rectangular Random Matrix Diffusions
30. ICLR 2025The Last Iterate Advantage: Empirical Auditing and Principled Heuristic Analysis of Differentially Private SGD
31. ICLR 2025The Utility and Complexity of In- and Out-of-Distribution Machine Unlearning
32. ICLR 2025Tighter Privacy Auditing of DP-SGD in the Hidden State Threat Model
33. ICLR 2025Towards hyperparameter-free optimization with differential privacy
34. ICML 2025Adapting to Linear Separable Subsets with Large-Margin in Differentially Private Learning
35. ICML 2025Approximate Differential Privacy of the $\ell_2$ Mechanism
36. ICML 2025Auditing $f$-differential privacy in one run
37. ICML 2025Breaking the $n^{1.5}$ Additive Error Barrier for Private and Efficient Graph Sparsification via Private Expander Decomposition
38. ICML 2025Breaking the Quadratic Barrier: Robust Cardinality Sketches for Adaptive Queries
39. ICML 2025Cape: Context-Aware Prompt Perturbation Mechanism with Differential Privacy
40. ICML 2025Certification for Differentially Private Prediction in Gradient-Based Training
41. ICML 2025Clients Collaborate: Flexible Differentially Private Federated Learning with Guaranteed Improvement of Utility-Privacy Trade-off
42. ICML 2025Differential Coding for Training-Free ANN-to-SNN Conversion
43. ICML 2025Differential Privacy Guarantees of Markov Chain Monte Carlo Algorithms
44. ICML 2025Differential Privacy Under Class Imbalance: Methods and Empirical Insights
45. ICML 2025Differentially Private Analysis for Binary Response Models: Optimality, Estimation, and Inference
46. ICML 2025Differentially Private Boxplots
47. ICML 2025Differentially Private Federated $k$-Means Clustering with Server-Side Data
48. ICML 2025Differentially Private Space-Efficient Algorithms for Counting Distinct Elements in the Turnstile Model
49. ICML 2025DMM: Distributed Matrix Mechanism for Differentially-Private Federated Learning Based on Constant-Overhead Linear Secret Resharing
50. ICML 2025Empirical Privacy Variance

FAQ

How many Differential Privacy papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

479 in total: 117 in 2023, 113 in 2024, 146 in 2025, 103 in 2026.

How many Differential Privacy papers are at NeurIPS 2026?

NeurIPS 2026 has 23 Differential Privacy papers, versus 66 the year before.

How many Differential Privacy papers are at ICLR 2026?

ICLR 2026 has 31 Differential Privacy papers, versus 29 the year before.

How many Differential Privacy papers are at ICML 2026?

ICML 2026 has 42 Differential Privacy papers, versus 47 the year before.

How many Differential Privacy papers are at CVPR 2026?

CVPR 2026 has 7 Differential Privacy papers, versus 4 the year before.

Which conference publishes the most Differential Privacy papers?

NeurIPS, with 217 papers from 2023 to 2026.