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

113 papers, page 1 of 3

1. CVPR 2024Affine Equivariant Networks Based on Differential Invariants
2. CVPR 2024All Rivers Run to the Sea: Private Learning with Asymmetric Flows
3. CVPR 2024Privacy-Preserving Optics for Enhancing Protection in Face De-Identification
4. ICLR 2024A Differentially Private Clustering Algorithm for Well-Clustered Graphs
5. ICLR 2024Decoupled Marked Temporal Point Process using Neural Ordinary Differential Equations
6. ICLR 2024Differentially Private SGD Without Clipping Bias: An Error-Feedback Approach
7. ICLR 2024Differentially Private Synthetic Data via Foundation Model APIs 1: Images
8. ICLR 2024DP-OPT: Make Large Language Model Your Privacy-Preserving Prompt Engineer
9. ICLR 2024Efficiently Computing Similarities to Private Datasets
10. ICLR 2024FedP3: Federated Personalized and Privacy-friendly Network Pruning under Model Heterogeneity
11. ICLR 2024Fixed-Budget Differentially Private Best Arm Identification
12. ICLR 2024Improved Analysis of Sparse Linear Regression in Local Differential Privacy Model
13. ICLR 2024Improving LoRA in Privacy-preserving Federated Learning
14. ICLR 2024LabelDP-Pro: Learning with Label Differential Privacy via Projections
15. ICLR 2024Learning No-Regret Sparse Generalized Linear Models with Varying Observation(s)
16. ICLR 2024Neural structure learning with stochastic differential equations
17. ICLR 2024On Differentially Private Federated Linear Contextual Bandits
18. ICLR 2024One-shot Empirical Privacy Estimation for Federated Learning
19. ICLR 2024Privacy Amplification for Matrix Mechanisms
20. ICLR 2024Privacy-Preserving In-Context Learning for Large Language Models
21. ICLR 2024Privacy-Preserving In-Context Learning with Differentially Private Few-Shot Generation
22. ICLR 2024Private Zeroth-Order Nonsmooth Nonconvex Optimization
23. ICLR 2024Privately Aligning Language Models with Reinforcement Learning
24. ICLR 2024SineNet: Learning Temporal Dynamics in Time-Dependent Partial Differential Equations
25. ICLR 2024Stable Neural Stochastic Differential Equations in Analyzing Irregular Time Series Data
26. ICLR 2024Tangent Transformers for Composition,Privacy and Removal
27. ICLR 2024The importance of feature preprocessing for differentially private linear optimization
28. ICLR 2024Tractable MCMC for Private Learning with Pure and Gaussian Differential Privacy
29. ICML 2024Auditing Private Prediction
30. ICML 2024Beyond the Calibration Point: Mechanism Comparison in Differential Privacy
31. ICML 2024Delving into Differentially Private Transformer
32. ICML 2024Diffusion Tempering Improves Parameter Estimation with Probabilistic Integrators for Ordinary Differential Equations
33. ICML 2024Hyperbolic Optimizer as a Dynamical System
34. ICML 2024Improved Communication-Privacy Trade-offs in $L_2$ Mean Estimation under Streaming Differential Privacy
35. ICML 2024Log Neural Controlled Differential Equations: The Lie Brackets Make A Difference
36. ICML 2024Mean Estimation in the Add-Remove Model of Differential Privacy
37. ICML 2024Mitigating Privacy Risk in Membership Inference by Convex-Concave Loss
38. ICML 2024Neural Collapse meets Differential Privacy: Curious behaviors of NoisyGD with Near-Perfect Representation Learning
39. ICML 2024Optimal Differentially Private Model Training with Public Data
40. ICML 2024Privacy Backdoors: Stealing Data with Corrupted Pretrained Models
41. ICML 2024Privacy Profiles for Private Selection
42. ICML 2024Privacy-Preserving Instructions for Aligning Large Language Models
43. ICML 2024Privately Learning Smooth Distributions on the Hypercube by Projections
44. ICML 2024Provable Privacy with Non-Private Pre-Processing
45. ICML 2024Shifted Interpolation for Differential Privacy
46. ICML 2024Split-and-Denoise: Protect large language model inference with local differential privacy
47. ICML 2024Stability-Informed Initialization of Neural Ordinary Differential Equations
48. ICML 2024Stabilizing Policy Gradients for Stochastic Differential Equations via Consistency with Perturbation Process
49. ICML 2024State-Constrained Zero-Sum Differential Games with One-Sided Information
50. ICML 2024The Privacy Power of Correlated Noise in Decentralized Learning

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.