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

431 papers, page 9 of 9

401. NeurIPS 2024Single Image Unlearning: Efficient Machine Unlearning in Multimodal Large Language Models
402. NeurIPS 2024SPEAR: Exact Gradient Inversion of Batches in Federated Learning
403. NeurIPS 2024SuperDeepFool: a new fast and accurate minimal adversarial attack
404. NeurIPS 2024The Limits of Differential Privacy in Online Learning
405. NeurIPS 2024Trap-MID: Trapdoor-based Defense against Model Inversion Attacks
406. NeurIPS 2024Truthful High Dimensional Sparse Linear Regression
407. NeurIPS 2024Unified Gradient-Based Machine Unlearning with Remain Geometry Enhancement
408. NeurIPS 2024Unified Mechanism-Specific Amplification by Subsampling and Group Privacy Amplification
409. NeurIPS 2024United We Stand, Divided We Fall: Fingerprinting Deep Neural Networks via Adversarial Trajectories
410. NeurIPS 2024Universal Exact Compression of Differentially Private Mechanisms
411. CVPR 2023DartBlur: Privacy Preservation With Detection Artifact Suppression
412. CVPR 2023Paired-Point Lifting for Enhanced Privacy-Preserving Visual Localization
413. CVPR 2023Privacy-Preserving Adversarial Facial Features
414. CVPR 2023Privacy-Preserving Representations Are Not Enough: Recovering Scene Content From Camera Poses
415. CVPR 2023SegLoc: Learning Segmentation-Based Representations for Privacy-Preserving Visual Localization
416. ICLR 2023CANIFE: Crafting Canaries for Empirical Privacy Measurement in Federated Learning
417. ICLR 2023Decepticons: Corrupted Transformers Breach Privacy in Federated Learning for Language Models
418. ICLR 2023Disparate Impact in Differential Privacy from Gradient Misalignment
419. ICLR 2023Regression with Label Differential Privacy
420. ICLR 2023Share Your Representation Only: Guaranteed Improvement of the Privacy-Utility Tradeoff in Federated Learning
421. ICML 2023Bayesian Estimation of Differential Privacy
422. ICML 2023Concurrent Shuffle Differential Privacy Under Continual Observation
423. ICML 2023GuardHFL: Privacy Guardian for Heterogeneous Federated Learning
424. ICML 2023HETAL: Efficient Privacy-preserving Transfer Learning with Homomorphic Encryption
425. ICML 2023Sketching Meets Differential Privacy: Fast Algorithm for Dynamic Kronecker Projection Maintenance
426. ICML 2023The Price of Differential Privacy under Continual Observation
427. ICML 2023The Saddle-Point Method in Differential Privacy
428. NeurIPS 2023Counting Distinct Elements Under Person-Level Differential Privacy
429. NeurIPS 2023Faster approximate subgraph counts with privacy
430. NeurIPS 2023k-Median Clustering via Metric Embedding: Towards Better Initialization with Differential Privacy
431. NeurIPS 2023Optimal Unbiased Randomizers for Regression with Label Differential Privacy

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.