Differential Privacy papers, 2023–2026
DP training
Scope: NeurIPS, ICLR, ICML and CVPR, 2023–2026. 479 papers are tagged with this topic.
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.
Papers per venue
Counts by year and venue
| Year | NeurIPS | ICLR | ICML | CVPR | Total |
|---|---|---|---|---|---|
| 2023 | 67 | 21 | 27 | 2 | 117 |
| 2024 | 61 | 25 | 24 | 3 | 113 |
| 2025 | 66 | 29 | 47 | 4 | 146 |
| 2026 | 23 | 31 | 42 | 7 | 103 |
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
217 papers, page 1 of 5
- NeurIPS 2026A Private Empirical Defense Against Privacy Audits
- NeurIPS 2026A Unified Framework for Adversary-Aware Differential Privacy Bounds
- NeurIPS 2026Aegis: Generative Gradient Masking for Privacy-Preserving Medical Federated Learning
- NeurIPS 2026Asymptotically Optimal Best Arm Identification with Fixed-Budget under Differential Privacy
- NeurIPS 2026Benchmarking Membership Privacy Risks in Preference-Based LLM Post-Training
- NeurIPS 2026Breakeven complexity: A new perspective on neural partial differential equation solvers
- NeurIPS 2026Differential Item Functioning as an Item-Level Diagnostic for LLM Benchmarks
- NeurIPS 2026Differential Vector Erasure: Unified Training-Free Concept Erasure for Flow Matching Models
- NeurIPS 2026DPrivBench: Benchmarking LLMs' Reasoning for Differential Privacy
- NeurIPS 2026𝑓-Differential Privacy Filters: Validity and Approximate Solutions
- NeurIPS 2026Improved Regret bounds in Tabular Reinforcement Learning under Local Differential Privacy
- NeurIPS 2026Lie Generator Networks for Nonlinear Partial Differential Equations
- NeurIPS 2026Neural Fractional Stochastic Differential Equations
- NeurIPS 2026Neural Quantum Spectral Operator Learning for Solving Partial Differential Equations
- NeurIPS 2026On Differential Private $\ell_1$, $\ell_2$ and $\ell_p^p$ Distance Queries
- NeurIPS 2026One-Shot Private Confidence Regions via Resampling
- NeurIPS 2026Optimal Algorithms for Fixed-Graph Multi-Attribution Privacy
- NeurIPS 2026Privacy-Preserving Retrieval-Augmented Generation with Plausible Deniability
- NeurIPS 2026Provable Robustness against Backdoor Attacks via the Primal-Dual Perspective on Differential Privacy
- NeurIPS 2026Random Neural Network Expressivity for Non-Linear Partial Differential Equations
- NeurIPS 2026Shuffle and Joint Differential Privacy for Generalized Linear Contextual Bandits
- NeurIPS 2026Sort, Partition, Randomize: Optimal Binary Hypothesis Testing under Local Differential Privacy
- NeurIPS 2026The Price of Locality in Label Privacy: Optimal Rates for Classification and Regression
- NeurIPS 2025A Generalized Binary Tree Mechanism for Private Approximation of All-Pair Shortest Distances
- NeurIPS 2025A Private Approximation of the 2nd-Moment Matrix of Any Subsamplable Input
- NeurIPS 2025Adaptive Data Analysis for Growing Data
- NeurIPS 2025Adaptive Sigmoid Clipping for Balancing the Direction–Magnitude Mismatch Trade-off in Differentially Private Learning
- NeurIPS 2025An Iterative Algorithm for Differentially Private $k$-PCA with Adaptive Noise
- NeurIPS 2025Blameless Users in a Clean Room: Defining Copyright Protection for Generative Models
- NeurIPS 2025Boundary-Value PDEs Meet Higher-Order Differential Topology-aware GNNs
- NeurIPS 2025Collapsing Taylor Mode Automatic Differentiation
- NeurIPS 2025Continual Release Moment Estimation with Differential Privacy
- NeurIPS 2025Continuous Simplicial Neural Networks
- NeurIPS 2025Controlling The Spread of Epidemics on Networks with Differential Privacy
- NeurIPS 2025Convex Approximation of Two-Layer ReLU Networks for Hidden State Differential Privacy
- NeurIPS 2025Dense Metric Depth Estimation via Event-based Differential Focus Volume Prompting
- NeurIPS 2025Differential Privacy for Euclidean Jordan Algebra with Applications to Private Symmetric Cone Programming
- NeurIPS 2025Differential Privacy on Fully Dynamic Streams
- NeurIPS 2025Differentially Private Bilevel Optimization: Efficient Algorithms with Near-Optimal Rates
- NeurIPS 2025Differentially Private Federated Low Rank Adaptation Beyond Fixed-Matrix
- NeurIPS 2025Differentially Private Gomory-Hu Trees
- NeurIPS 2025Differentially Private High-dimensional Variable Selection via Integer Programming
- NeurIPS 2025Differentially Private Quantiles with Smaller Error
- NeurIPS 2025Differentially Private Relational Learning with Entity-level Privacy Guarantees
- NeurIPS 2025DIFFSSR: Stereo Image Super-resolution Using Differential Transformer
- NeurIPS 2025Discovering Symbolic Partial Differential Equation by Abductive Learning
- NeurIPS 2025Do You Really Need Public Data? Surrogate Public Data for Differential Privacy on Tabular Data
- NeurIPS 2025FedSVD: Adaptive Orthogonalization for Private Federated Learning with LoRA
- NeurIPS 2025GeoClip: Geometry-Aware Clipping for Differentially Private SGD
- NeurIPS 2025How Well Can Differential Privacy Be Audited in One Run?
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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.