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

479 papers, page 10 of 10

451. NeurIPS 2023Minimax Risks and Optimal Procedures for Estimation under Functional Local Differential Privacy
452. NeurIPS 2023Nearly Tight Bounds For Differentially Private Multiway Cut
453. NeurIPS 2023Neural Fields with Hard Constraints of Arbitrary Differential Order
454. NeurIPS 2023Neural Graph Generation from Graph Statistics
455. NeurIPS 2023Offline Reinforcement Learning with Differential Privacy
456. NeurIPS 2023On Computing Pairwise Statistics with Local Differential Privacy
457. NeurIPS 2023On the Complexity of Differentially Private Best-Arm Identification with Fixed Confidence
458. NeurIPS 2023On the Gini-impurity Preservation For Privacy Random Forests
459. NeurIPS 2023Optimal privacy guarantees for a relaxed threat model: Addressing sub-optimal adversaries in differentially private machine learning
460. NeurIPS 2023Optimal Unbiased Randomizers for Regression with Label Differential Privacy
461. NeurIPS 2023Post-processing Private Synthetic Data for Improving Utility on Selected Measures
462. NeurIPS 2023Practical Differentially Private Hyperparameter Tuning with Subsampling
463. NeurIPS 2023Privacy Amplification via Compression: Achieving the Optimal Privacy-Accuracy-Communication Trade-off in Distributed Mean Estimation
464. NeurIPS 2023Privacy Auditing with One (1) Training Run
465. NeurIPS 2023Private (Stochastic) Non-Convex Optimization Revisited: Second-Order Stationary Points and Excess Risks
466. NeurIPS 2023Private Distribution Learning with Public Data: The View from Sample Compression
467. NeurIPS 2023Private Everlasting Prediction
468. NeurIPS 2023Probabilistic Exponential Integrators
469. NeurIPS 2023Scaling Up Differentially Private LASSO Regularized Logistic Regression via Faster Frank-Wolfe Iterations
470. NeurIPS 2023Smooth Flipping Probability for Differential Private Sign Random Projection Methods
471. NeurIPS 2023Sparsity-Preserving Differentially Private Training of Large Embedding Models
472. NeurIPS 2023The Bayesian Stability Zoo
473. NeurIPS 2023The Target-Charging Technique for Privacy Analysis across Interactive Computations
474. NeurIPS 2023Training Private Models That Know What They Don’t Know
475. NeurIPS 2023Unbounded Differentially Private Quantile and Maximum Estimation
476. NeurIPS 2023Unified Enhancement of Privacy Bounds for Mixture Mechanisms via $f$-Differential Privacy
477. NeurIPS 2023Unified Lower Bounds for Interactive High-dimensional Estimation under Information Constraints
478. NeurIPS 2023Unleashing the Power of Randomization in Auditing Differentially Private ML
479. NeurIPS 2023User-Level Differential Privacy With Few Examples Per User

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.