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

23 papers, page 1 of 1

1. NeurIPS 2026A Private Empirical Defense Against Privacy Audits
2. NeurIPS 2026A Unified Framework for Adversary-Aware Differential Privacy Bounds
3. NeurIPS 2026Aegis: Generative Gradient Masking for Privacy-Preserving Medical Federated Learning
4. NeurIPS 2026Asymptotically Optimal Best Arm Identification with Fixed-Budget under Differential Privacy
5. NeurIPS 2026Benchmarking Membership Privacy Risks in Preference-Based LLM Post-Training
6. NeurIPS 2026Breakeven complexity: A new perspective on neural partial differential equation solvers
7. NeurIPS 2026Differential Item Functioning as an Item-Level Diagnostic for LLM Benchmarks
8. NeurIPS 2026Differential Vector Erasure: Unified Training-Free Concept Erasure for Flow Matching Models
9. NeurIPS 2026DPrivBench: Benchmarking LLMs' Reasoning for Differential Privacy
10. NeurIPS 2026𝑓-Differential Privacy Filters: Validity and Approximate Solutions
11. NeurIPS 2026Improved Regret bounds in Tabular Reinforcement Learning under Local Differential Privacy
12. NeurIPS 2026Lie Generator Networks for Nonlinear Partial Differential Equations
13. NeurIPS 2026Neural Fractional Stochastic Differential Equations
14. NeurIPS 2026Neural Quantum Spectral Operator Learning for Solving Partial Differential Equations
15. NeurIPS 2026On Differential Private $\ell_1$, $\ell_2$ and $\ell_p^p$ Distance Queries
16. NeurIPS 2026One-Shot Private Confidence Regions via Resampling
17. NeurIPS 2026Optimal Algorithms for Fixed-Graph Multi-Attribution Privacy
18. NeurIPS 2026Privacy-Preserving Retrieval-Augmented Generation with Plausible Deniability
19. NeurIPS 2026Provable Robustness against Backdoor Attacks via the Primal-Dual Perspective on Differential Privacy
20. NeurIPS 2026Random Neural Network Expressivity for Non-Linear Partial Differential Equations
21. NeurIPS 2026Shuffle and Joint Differential Privacy for Generalized Linear Contextual Bandits
22. NeurIPS 2026Sort, Partition, Randomize: Optimal Binary Hypothesis Testing under Local Differential Privacy
23. NeurIPS 2026The Price of Locality in Label Privacy: Optimal Rates for Classification and Regression

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.