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

146 papers, page 3 of 3

101. NeurIPS 2025Differentially Private Relational Learning with Entity-level Privacy Guarantees
102. NeurIPS 2025DIFFSSR: Stereo Image Super-resolution Using Differential Transformer
103. NeurIPS 2025Discovering Symbolic Partial Differential Equation by Abductive Learning
104. NeurIPS 2025Do You Really Need Public Data? Surrogate Public Data for Differential Privacy on Tabular Data
105. NeurIPS 2025FedSVD: Adaptive Orthogonalization for Private Federated Learning with LoRA
106. NeurIPS 2025GeoClip: Geometry-Aware Clipping for Differentially Private SGD
107. NeurIPS 2025How Well Can Differential Privacy Be Audited in One Run?
108. NeurIPS 2025Instance-Optimality for Private KL Distribution Estimation
109. NeurIPS 2025Learning Differential Pyramid Representation for Tone Mapping
110. NeurIPS 2025Locally Optimal Private Sampling: Beyond the Global Minimax
111. NeurIPS 2025Mitigating the Privacy–Utility Trade-off in Decentralized Federated Learning via f-Differential Privacy
112. NeurIPS 2025Multi-Class Support Vector Machine with Differential Privacy
113. NeurIPS 2025Nearly-Linear Time Private Hypothesis Selection with the Optimal Approximation Factor
114. NeurIPS 2025Neural Fractional Attention Differential Equations
115. NeurIPS 2025On Traceability in $\ell_p$ Stochastic Convex Optimization
116. NeurIPS 2025Online Locally Differentially Private Conformal Prediction via Binary Inquiries
117. NeurIPS 2025Online robust locally differentially private learning for nonparametric regression
118. NeurIPS 2025Optimal Best Arm Identification under Differential Privacy
119. NeurIPS 2025Optimal Regret of Bandits under Differential Privacy
120. NeurIPS 2025PREAMBLE: Private and Efficient Aggregation via Block Sparse Vectors
121. NeurIPS 2025Privacy amplification by random allocation
122. NeurIPS 2025Private Continual Counting of Unbounded Streams
123. NeurIPS 2025Private Evolution Converges
124. NeurIPS 2025Private Geometric Median in Nearly-Linear Time
125. NeurIPS 2025Private Hyperparameter Tuning with Ex-Post Guarantee
126. NeurIPS 2025Private Online Learning against an Adaptive Adversary: Realizable and Agnostic Settings
127. NeurIPS 2025Private Set Union with Multiple Contributions
128. NeurIPS 2025Private Statistical Estimation via Truncation
129. NeurIPS 2025Private Training Large-scale Models with Efficient DP-SGD
130. NeurIPS 2025Private Zeroth-Order Optimization with Public Data
131. NeurIPS 2025Projective Equivariant Networks via Second-order Fundamental Differential Invariants
132. NeurIPS 2025Purifying Approximate Differential Privacy with Randomized Post-processing
133. NeurIPS 2025Query-Efficient Locally Private Hypothesis Selection via the Scheffe Graph
134. NeurIPS 2025Sequentially Auditing Differential Privacy
135. NeurIPS 2025Setting $\varepsilon$ is not the Issue in Differential Privacy
136. NeurIPS 2025Sketched Gaussian Mechanism for Private Federated Learning
137. NeurIPS 2025Solving Partial Differential Equations via Radon Neural Operator
138. NeurIPS 2025Sum Estimation under Personalized Local Differential Privacy
139. NeurIPS 2025Synthesize Privacy-Preserving High-Resolution Images via Private Textual Intermediaries
140. NeurIPS 2025The Gaussian Mixing Mechanism: Renyi Differential Privacy via Gaussian Sketches
141. NeurIPS 2025Tight Bounds for Answering Adaptively Chosen Concentrated Queries
142. NeurIPS 2025Time-uniform and Asymptotic Confidence Sequence of Quantile under Local Differential Privacy
143. NeurIPS 2025UEPI: Universal Energy-Behavior-Preserving Integrators for Energy Conservative/Dissipative Differential Equations
144. NeurIPS 2025Unifying Re-Identification, Attribute Inference, and Data Reconstruction Risks in Differential Privacy
145. NeurIPS 2025Wavy Transformer
146. NeurIPS 2025⁠When Data Can't Meet: Estimating Correlation Across Privacy Barriers

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.