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

24 papers, page 1 of 1

1. ICML 2024Auditing Private Prediction
2. ICML 2024Beyond the Calibration Point: Mechanism Comparison in Differential Privacy
3. ICML 2024Delving into Differentially Private Transformer
4. ICML 2024Diffusion Tempering Improves Parameter Estimation with Probabilistic Integrators for Ordinary Differential Equations
5. ICML 2024Hyperbolic Optimizer as a Dynamical System
6. ICML 2024Improved Communication-Privacy Trade-offs in $L_2$ Mean Estimation under Streaming Differential Privacy
7. ICML 2024Log Neural Controlled Differential Equations: The Lie Brackets Make A Difference
8. ICML 2024Mean Estimation in the Add-Remove Model of Differential Privacy
9. ICML 2024Mitigating Privacy Risk in Membership Inference by Convex-Concave Loss
10. ICML 2024Neural Collapse meets Differential Privacy: Curious behaviors of NoisyGD with Near-Perfect Representation Learning
11. ICML 2024Optimal Differentially Private Model Training with Public Data
12. ICML 2024Privacy Backdoors: Stealing Data with Corrupted Pretrained Models
13. ICML 2024Privacy Profiles for Private Selection
14. ICML 2024Privacy-Preserving Instructions for Aligning Large Language Models
15. ICML 2024Privately Learning Smooth Distributions on the Hypercube by Projections
16. ICML 2024Provable Privacy with Non-Private Pre-Processing
17. ICML 2024Shifted Interpolation for Differential Privacy
18. ICML 2024Split-and-Denoise: Protect large language model inference with local differential privacy
19. ICML 2024Stability-Informed Initialization of Neural Ordinary Differential Equations
20. ICML 2024Stabilizing Policy Gradients for Stochastic Differential Equations via Consistency with Perturbation Process
21. ICML 2024State-Constrained Zero-Sum Differential Games with One-Sided Information
22. ICML 2024The Privacy Power of Correlated Noise in Decentralized Learning
23. ICML 2024Tuning-free Estimation and Inference of Cumulative Distribution Function under Local Differential Privacy
24. ICML 2024Unveiling Privacy, Memorization, and Input Curvature Links

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.