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

155 papers, page 3 of 4

101. NeurIPS 2025DRIFT: Dynamic Rule-Based Defense with Injection Isolation for Securing LLM Agents
102. NeurIPS 2025Exploring the limits of strong membership inference attacks on large language models
103. NeurIPS 2025FedRW: Efficient Privacy-Preserving Data Reweighting for Enhancing Federated Learning of Language Models
104. NeurIPS 2025FLUX: Efficient Descriptor-Driven Clustered Federated Learning under Arbitrary Distribution Shifts
105. NeurIPS 2025FracFace: Breaking The Visual Clues—Fractal-Based Privacy-Preserving Face Recognition
106. NeurIPS 2025GeoClip: Geometry-Aware Clipping for Differentially Private SGD
107. NeurIPS 2025Harnessing the Universal Geometry of Embeddings
108. NeurIPS 2025How Well Can Differential Privacy Be Audited in One Run?
109. NeurIPS 2025Instance-Optimality for Private KL Distribution Estimation
110. NeurIPS 2025InvisibleInk: High-Utility and Low-Cost Text Generation with Differential Privacy
111. NeurIPS 2025Locally Optimal Private Sampling: Beyond the Global Minimax
112. NeurIPS 2025Machine Unlearning via Task Simplex Arithmetic
113. NeurIPS 2025Mitigating the Privacy–Utility Trade-off in Decentralized Federated Learning via f-Differential Privacy
114. NeurIPS 2025MPCache: MPC-Friendly KV Cache Eviction for Efficient Private LLM Inference
115. NeurIPS 2025Multi-Class Support Vector Machine with Differential Privacy
116. NeurIPS 2025OASIS: One-Shot Federated Graph Learning via Wasserstein Assisted Knowledge Integration
117. NeurIPS 2025ObCLIP: Oblivious CLoud-Device Hybrid Image Generation with Privacy Preservation
118. NeurIPS 2025On the Sample Complexity of Differentially Private Policy Optimization
119. NeurIPS 2025OpenGU: A Comprehensive Benchmark for Graph Unlearning
120. NeurIPS 2025Optimal Best Arm Identification under Differential Privacy
121. NeurIPS 2025Optimal Regret of Bandits under Differential Privacy
122. NeurIPS 2025Perturb a Model, Not an Image: Towards Robust Privacy Protection via Anti-Personalized Diffusion Models
123. NeurIPS 2025Practical Bayes-Optimal Membership Inference Attacks
124. NeurIPS 2025Privacy amplification by random allocation
125. NeurIPS 2025Privacy Reasoning in Ambiguous Contexts
126. NeurIPS 2025Private Continual Counting of Unbounded Streams
127. NeurIPS 2025Private Geometric Median in Nearly-Linear Time
128. NeurIPS 2025Private Hyperparameter Tuning with Ex-Post Guarantee
129. NeurIPS 2025Private Set Union with Multiple Contributions
130. NeurIPS 2025Private Zeroth-Order Optimization with Public Data
131. NeurIPS 2025Probabilistic Reasoning with LLMs for Privacy Risk Estimation
132. NeurIPS 2025Purifying Approximate Differential Privacy with Randomized Post-processing
133. NeurIPS 2025Query-Efficient Locally Private Hypothesis Selection via the Scheffe Graph
134. NeurIPS 2025Rethinking Fair Federated Learning from Parameter and Client View
135. NeurIPS 2025Rethinking the Role of Verbatim Memorization in LLM Privacy
136. NeurIPS 2025Rewind-to-Delete: Certified Machine Unlearning for Nonconvex Functions
137. NeurIPS 2025RUAGO: Effective and Practical Retain-Free Unlearning via Adversarial Attack and OOD Generator
138. NeurIPS 2025Second-Order Convergence in Private Stochastic Non-Convex Optimization
139. NeurIPS 2025Secure and Confidential Certificates of Online Fairness
140. NeurIPS 2025Sequentially Auditing Differential Privacy
141. NeurIPS 2025Setting $\varepsilon$ is not the Issue in Differential Privacy
142. NeurIPS 2025Sketched Gaussian Mechanism for Private Federated Learning
143. NeurIPS 2025Subgraph Federated Learning via Spectral Methods
144. NeurIPS 2025Sum Estimation under Personalized Local Differential Privacy
145. NeurIPS 2025Synthesize Privacy-Preserving High-Resolution Images via Private Textual Intermediaries
146. NeurIPS 2025The Unseen Threat: Residual Knowledge in Machine Unlearning under Perturbed Samples
147. NeurIPS 2025Time-uniform and Asymptotic Confidence Sequence of Quantile under Local Differential Privacy
148. NeurIPS 2025TokenSwap: A Lightweight Method to Disrupt Memorized Sequences in LLMs
149. NeurIPS 2025Toward Efficient Inference Attacks: Shadow Model Sharing via Mixture-of-Experts
150. NeurIPS 2025Train to Defend: First Defense Against Cryptanalytic Neural Network Parameter Extraction Attacks

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.