Social aspects · privacy papers, 2023–2026

Key findings

• Social aspects · privacy went from 21 papers in 2023 to 138 in 2026, roughly 6.6x in three years.
• NeurIPS publishes the most Social aspects · privacy work: 215 papers from 2023 to 2026, 50% 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 93 in 2026.
• Among the 5 topics under Alignment and Responsible AI, it ranks #4 by 2026 paper count; the fastest grower in the group, Social aspects · safety, is up 93x versus 6.6x here.

Representative papers

Spread across years and venues so every edition shows up

• NeurIPS 2026Assessing Per-Sample Membership Inference Vulnerability without Retraining
• ICML 2026Accuracy-First Rényi Differential Privacy and Post-Processing Immunity
• ICLR 2026Mitigating Privacy Risk via Forget Set-Free Unlearning
• CVPR 2026Protego User-Centric Pose-Invariant Privacy Protection Against Face Recognition-Induced Digital Footprint
• NeurIPS 2025A Generalized Binary Tree Mechanism for Private Approximation of All-Pair Shortest Distances
• ICML 2025Breaking the $n^{1.5}$ Additive Error Barrier for Private and Efficient Graph Sparsification via Private Expander Decomposition
• ICLR 2025Machine Unlearning via Simulated Oracle Matching
• CVPR 2025Enhancing Facial Privacy Protection via Weakening Diffusion Purification
• NeurIPS 2024Adaptive Randomized Smoothing: Certified Adversarial Robustness for Multi-Step Defences
• ICML 2024Privacy Preserving Adaptive Experiment Design
• ICLR 2024Beyond Memorization: Violating Privacy via Inference with Large Language Models
• CVPR 2024Validating Privacy-Preserving Face Recognition under a Minimum Assumption
• NeurIPS 2023Faster approximate subgraph counts with privacy
• ICML 2023GuardHFL: Privacy Guardian for Heterogeneous Federated Learning
• ICLR 2023Decepticons: Corrupted Transformers Breach Privacy in Federated Learning for Language Models
• CVPR 2023Privacy-Preserving Representations Are Not Enough: Recovering Scene Content From Camera Poses
• NeurIPS 2026Asymmetric Invertible Threat: Learning Reversible Privacy Defense for Face Recognition
• ICML 2026Accurate, Private, Secure, Federated U-statistics with Higher Degree
• ICLR 2026Measuring Physical-World Privacy Awareness of Large Language Models: An Evaluation Benchmark
• CVPR 2026LDP-Slicing Local Differential Privacy for Images via Randomized Bit-Plane Slicing

All Social aspects · privacy papers

181 papers, page 3 of 4

101. ICML 2025Cape: Context-Aware Prompt Perturbation Mechanism with Differential Privacy
102. ICML 2025Certification for Differentially Private Prediction in Gradient-Based Training
103. ICML 2025Certified Unlearning for Neural Networks
104. ICML 2025Clients Collaborate: Flexible Differentially Private Federated Learning with Guaranteed Improvement of Utility-Privacy Trade-off
105. ICML 2025Contrastive Private Data Synthesis via Weighted Multi-PLM Fusion
106. ICML 2025Differential Privacy Under Class Imbalance: Methods and Empirical Insights
107. ICML 2025Differentially Private Analysis for Binary Response Models: Optimality, Estimation, and Inference
108. ICML 2025Differentially Private Boxplots
109. ICML 2025Differentially Private Federated $k$-Means Clustering with Server-Side Data
110. ICML 2025Differentially Private Space-Efficient Algorithms for Counting Distinct Elements in the Turnstile Model
111. ICML 2025Distributed Differentially Private Data Analytics via Secure Sketching
112. ICML 2025DMM: Distributed Matrix Mechanism for Differentially-Private Federated Learning Based on Constant-Overhead Linear Secret Resharing
113. ICML 2025DRAG: Data Reconstruction Attack using Guided Diffusion
114. ICML 2025Editable Concept Bottleneck Models
115. ICML 2025Efficient Source-free Unlearning via Energy-Guided Data Synthesis and Discrimination-Aware Multitask Optimization
116. ICML 2025EgoPrivacy: What Your First-Person Camera Says About You?
117. ICML 2025Empirical Privacy Variance
118. ICML 2025EncryptedLLM: Privacy-Preserving Large Language Model Inference via GPU-Accelerated Fully Homomorphic Encryption
119. ICML 2025Fast Exact Unlearning for In-Context Learning Data for LLMs
120. ICML 2025Faster Rates for Private Adversarial Bandits
121. ICML 2025Federated Disentangled Tuning with Textual Prior Decoupling and Visual Dynamic Adaptation
122. ICML 2025FOCoOp: Enhancing Out-of-Distribution Robustness in Federated Prompt Learning for Vision-Language Models
123. ICML 2025GHOST: Generalizable One-Shot Federated Graph Learning with Proxy-Based Topology Knowledge Retention
124. ICML 2025Going Deeper into Locally Differentially Private Graph Neural Networks
125. ICML 2025Gradient Inversion of Multimodal Models
126. ICML 2025Improved Sample Complexity for Private Nonsmooth Nonconvex Optimization
127. ICML 2025It's My Data Too: Private ML for Datasets with Multi-User Training Examples
128. ICML 2025Janus: Dual-Server Multi-Round Secure Aggregation with Verifiability for Federated Learning
129. ICML 2025Kona: An Efficient Privacy-Preservation Framework for KNN Classification by Communication Optimization
130. ICML 2025Leveraging Model Guidance to Extract Training Data from Personalized Diffusion Models
131. ICML 2025Leveraging Per-Instance Privacy for Machine Unlearning
132. ICML 2025Leveraging Randomness in Model and Data Partitioning for Privacy Amplification
133. ICML 2025Lightweight Protocols for Distributed Private Quantile Estimation
134. ICML 2025Local Pan-privacy for Federated Analytics
135. ICML 2025Noisy SIGNSGD Is More Differentially Private Than You (Might) Think
136. ICML 2025On the Private Estimation of Smooth Transport Maps
137. ICML 2025Optimal Survey Design for Private Mean Estimation
138. ICML 2025Optimizing Noise Distributions for Differential Privacy
139. ICML 2025PASS: Private Attributes Protection with Stochastic Data Substitution
140. ICML 2025PCEvolve: Private Contrastive Evolution for Synthetic Dataset Generation via Few-Shot Private Data and Generative APIs
141. ICML 2025Plausible Token Amplification for Improving Accuracy of Differentially Private In-Context Learning Based on Implicit Bayesian Inference
142. ICML 2025Position: Contextual Integrity is Inadequately Applied to Language Models
143. ICML 2025Privacy Amplification by Structured Subsampling for Deep Differentially Private Time Series Forecasting
144. ICML 2025Privacy Amplification Through Synthetic Data: Insights from Linear Regression
145. ICML 2025Privacy-Preserving Federated Convex Optimization: Balancing Partial-Participation and Efficiency via Noise Cancellation
146. ICML 2025Private Federated Learning using Preference-Optimized Synthetic Data
147. ICML 2025Private Lossless Multiple Release
148. ICML 2025Private Model Personalization Revisited
149. ICML 2025Rethinking the Temperature for Federated Heterogeneous Distillation
150. ICML 2025Scalable Private Partition Selection via Adaptive Weighting

FAQ

How many Social aspects · privacy papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

431 in total: 21 in 2023, 117 in 2024, 155 in 2025, 138 in 2026.

How many Social aspects · privacy papers are at NeurIPS 2026?

NeurIPS 2026 has 44 Social aspects · privacy papers, versus 80 the year before.

How many Social aspects · privacy papers are at ICLR 2026?

ICLR 2026 has 2 Social aspects · privacy papers, versus 2 the year before.

How many Social aspects · privacy papers are at ICML 2026?

ICML 2026 has 90 Social aspects · privacy papers, versus 71 the year before.

How many Social aspects · privacy papers are at CVPR 2026?

CVPR 2026 has 2 Social aspects · privacy papers, versus 2 the year before.

Which conference publishes the most Social aspects · privacy papers?

NeurIPS, with 215 papers from 2023 to 2026.