{"total":73,"rows":[{"id":"2301.13188","title":"Extracting Training Data from Diffusion Models","created":"2023-01-30","cited_by_count":732,"area":"diffusion"},{"id":"2302.01316","title":"Are Diffusion Models Vulnerable to Membership Inference Attacks?","created":"2023-02-02","cited_by_count":136,"area":"diffusion"},{"id":"2210.09929","title":"Differentially Private Diffusion Models","created":"2022-10-18","cited_by_count":119,"area":"diffusion"},{"id":"2302.03262","title":"Membership Inference Attacks against Diffusion Models","created":"2023-02-07","cited_by_count":86,"area":"diffusion"},{"id":"2302.13861","title":"Differentially Private Diffusion Models Generate Useful Synthetic Images","created":"2023-02-27","cited_by_count":86,"area":"diffusion"},{"id":"2401.05779","title":"Erasing Undesirable Influence in Diffusion Models","created":"2024-01-11","cited_by_count":57,"area":"diffusion"},{"id":"2404.00922","title":"Towards Memorization-Free Diffusion Models","created":"2024-04-01","cited_by_count":50,"area":"diffusion"},{"id":"2301.09956","title":"Membership Inference of Diffusion Models","created":"2023-01-24","cited_by_count":46,"area":"diffusion"},{"id":"2308.06405","title":"White-box Membership Inference Attacks against Diffusion Models","created":"2023-08-11","cited_by_count":42,"area":"diffusion"},{"id":"2312.08207","title":"Black-box Membership Inference Attacks against Fine-tuned Diffusion Models","created":"2023-12-13","cited_by_count":35,"area":"diffusion"},{"id":"2408.03400","title":"Attacks and Defenses for Generative Diffusion Models: A Comprehensive Survey","created":"2024-08-06","cited_by_count":32,"area":"diffusion"},{"id":"2305.15759","title":"DP-LDMs: Differentially Private Latent Diffusion Models","created":"2023-05-25","cited_by_count":29,"area":"diffusion"},{"id":"2305.07644","title":"Beware of diffusion models for synthesizing medical images -- A comparison with GANs in terms of memorizing brain MRI and chest x-ray images","created":"2023-05-12","cited_by_count":23,"area":"diffusion"},{"id":"2409.11219","title":"Score Forgetting Distillation: A Swift, Data-Free Method for Machine Unlearning in Diffusion Models","created":"2024-09-17","cited_by_count":23,"area":"diffusion"},{"id":"2406.01355","title":"Differentially Private Fine-Tuning of Diffusion Models","created":"2024-06-03","cited_by_count":20,"area":"diffusion"},{"id":"2306.01322","title":"Privacy Distillation: Reducing Re-identification Risk of Multimodal Diffusion Models","created":"2023-06-02","cited_by_count":18,"area":"diffusion"},{"id":"2308.01937","title":"Training Data Protection with Compositional Diffusion Models","created":"2023-08-02","cited_by_count":17,"area":"diffusion"},{"id":"2403.09450","title":"Shake to Leak: Fine-tuning Diffusion Models Can Amplify the Generative Privacy Risk","created":"2024-03-14","cited_by_count":17,"area":"diffusion"},{"id":"2307.16680","title":"On the Trustworthiness Landscape of State-of-the-art Generative Models: A Survey and Outlook","created":"2023-07-31","cited_by_count":15,"area":"diffusion"},{"id":"2311.12850","title":"PrivImage: Differentially Private Synthetic Image Generation using Diffusion Models with Semantic-Aware Pretraining","created":"2023-10-19","cited_by_count":13,"area":"diffusion"},{"id":"2407.15328","title":"Iterative Ensemble Training with Anti-Gradient Control for Mitigating Memorization in Diffusion Models","created":"2024-07-22","cited_by_count":12,"area":"diffusion"},{"id":"2502.05446","title":"Stochastic Forward-Backward Deconvolution: Training Diffusion Models with Finite Noisy Datasets","created":"2025-02-08","cited_by_count":11,"area":"diffusion"},{"id":"2302.07801","title":"Data Forensics in Diffusion Models: A Systematic Analysis of Membership Privacy","created":"2023-02-15","cited_by_count":10,"area":"diffusion"},{"id":"2410.22971","title":"Private Synthetic Text Generation with Diffusion Models","created":"2024-10-30","cited_by_count":10,"area":"diffusion"},{"id":"2405.01494","title":"Navigating Heterogeneity and Privacy in One-Shot Federated Learning with Diffusion Models","created":"2024-05-02","cited_by_count":7,"area":"diffusion"},{"id":"2407.16405","title":"On Differentially Private 3D Medical Image Synthesis with Controllable Latent Diffusion Models","created":"2024-07-23","cited_by_count":7,"area":"diffusion"},{"id":"2504.01395","title":"From Easy to Hard: Building a Shortcut for Differentially Private Image Synthesis","created":"2025-04-02","cited_by_count":7,"area":"diffusion"},{"id":"2403.07842","title":"DP-TLDM: Differentially Private Tabular Latent Diffusion Model","created":"2024-03-12","cited_by_count":5,"area":"diffusion"},{"id":"2306.01363","title":"Quantifying Sample Anonymity in Score-Based Generative Models with Adversarial Fingerprinting","created":"2023-06-02","cited_by_count":4,"area":"diffusion"},{"id":"2306.05208","title":"PriSampler: Mitigating Property Inference of Diffusion Models","created":"2023-06-08","cited_by_count":4,"area":"diffusion"},{"id":"2312.04692","title":"Diffence: Fencing Membership Privacy With Diffusion Models","created":"2023-12-07","cited_by_count":4,"area":"diffusion"},{"id":"2311.09355","title":"Privacy Threats in Stable Diffusion Models","created":"2023-11-15","cited_by_count":3,"area":"diffusion"},{"id":"2405.18627","title":"PureGen: Universal Data Purification for Train-Time Poison Defense via Generative Model Dynamics","created":"2024-05-28","cited_by_count":3,"area":"diffusion"},{"id":"2409.05414","title":"CipherDM: Secure Three-Party Inference for Diffusion Model Sampling","created":"2024-09-09","cited_by_count":3,"area":"diffusion"},{"id":"2409.07025","title":"CPSample: Classifier Protected Sampling for Guarding Training Data During Diffusion","created":"2024-09-11","cited_by_count":3,"area":"diffusion"},{"id":"2410.16657","title":"Dual-Model Defense: Safeguarding Diffusion Models from Membership Inference Attacks through Disjoint Data Splitting","created":"2024-10-22","cited_by_count":3,"area":"diffusion"},{"id":"2411.11197","title":"Stealing Training Graphs from Graph Neural Networks","created":"2024-11-17","cited_by_count":3,"area":"diffusion"},{"id":"2509.22723","title":"Responsible Diffusion: A Comprehensive Survey on Safety, Ethics, and Trust in Diffusion Models","created":"2025-09-25","cited_by_count":3,"area":"diffusion"},{"id":"2403.07588","title":"Visual Privacy Auditing with Diffusion Models","created":"2024-03-12","cited_by_count":2,"area":"diffusion"},{"id":"2406.05257","title":"Efficient Differentially Private Fine-Tuning of Diffusion Models","created":"2024-06-07","cited_by_count":2,"area":"diffusion"},{"id":"2408.14738","title":"Learning Differentially Private Diffusion Models via Stochastic Adversarial Distillation","created":"2024-08-27","cited_by_count":2,"area":"diffusion"},{"id":"2412.16083","title":"Federated Diffusion Modeling with Differential Privacy for Tabular Data Synthesis","created":"2024-12-20","cited_by_count":2,"area":"diffusion"},{"id":"2504.04582","title":"Your Image Generator Is Your New Private Dataset","created":"2025-04-06","cited_by_count":2,"area":"diffusion"},{"id":"2505.02824","title":"Towards Dataset Copyright Evasion Attack against Personalized Text-to-Image Diffusion Models","created":"2025-05-05","cited_by_count":2,"area":"diffusion"},{"id":"2601.03701","title":"Inference Attacks Against Graph Generative Diffusion Models","created":"2026-01-07","cited_by_count":2,"area":"diffusion"},{"id":"2312.01201","title":"PAC Privacy Preserving Diffusion Models","created":"2023-12-02","cited_by_count":1,"area":"diffusion"},{"id":"2411.03053","title":"Gradient-Guided Conditional Diffusion Models for Private Image Reconstruction: Analyzing Adversarial Impacts of Differential Privacy and Denoising","created":"2024-11-05","cited_by_count":1,"area":"diffusion"},{"id":"2411.18956","title":"Random Sampling for Diffusion-based Adversarial Purification","created":"2024-11-28","cited_by_count":1,"area":"diffusion"},{"id":"2506.02371","title":"SFBD Flow: A Continuous-Optimization Framework for Training Diffusion Models with Noisy Samples","created":"2025-06-03","cited_by_count":1,"area":"diffusion"},{"id":"2507.11441","title":"Implementing Adaptations for Vision AutoRegressive Model","created":"2025-07-15","cited_by_count":1,"area":"diffusion"},{"id":"2508.04208","title":"DP-DocLDM: Differentially Private Document Image Generation using Latent Diffusion Models","created":"2025-08-06","cited_by_count":1,"area":"diffusion"},{"id":"2509.14225","title":"Defending Diffusion Models Against Membership Inference Attacks via Higher-Order Langevin Dynamics","created":"2025-09-17","cited_by_count":1,"area":"diffusion"},{"id":"2509.22352","title":"SurvDiff: A Diffusion Model for Generating Synthetic Data in Survival Analysis","created":"2025-09-26","cited_by_count":1,"area":"diffusion"},{"id":"2512.07342","title":"PrivORL: Differentially Private Synthetic Dataset for Offline Reinforcement Learning","created":"2025-12-08","cited_by_count":1,"area":"diffusion"},{"id":"2602.22610","title":"DP-aware AdaLN-Zero: Taming Conditioning-Induced Heavy-Tailed Gradients in Differentially Private Diffusion","created":"2026-02-26","cited_by_count":1,"area":"diffusion"},{"id":"2010.00638","title":"Tabular GANs for uneven distribution","created":"2020-10-01","cited_by_count":0,"area":"diffusion"},{"id":"2403.16365","title":"Generating Potent Poisons and Backdoors from Scratch with Guided Diffusion","created":"2024-03-25","cited_by_count":0,"area":"diffusion"},{"id":"2411.14639","title":"Differentially Private Adaptation of Diffusion Models via Noisy Aggregated Embeddings","created":"2024-11-22","cited_by_count":0,"area":"diffusion"},{"id":"2502.09434","title":"Redistribute Ensemble Training for Mitigating Memorization in Diffusion Models","created":"2025-02-13","cited_by_count":0,"area":"diffusion"},{"id":"2504.00952","title":"Personalized Federated Training of Diffusion Models with Privacy Guarantees","created":"2025-04-01","cited_by_count":0,"area":"diffusion"},{"id":"2512.00638","title":"Privacy Preserving Diffusion Models for Mixed-Type Tabular Data Generation","created":"2025-11-29","cited_by_count":0,"area":"diffusion"},{"id":"2603.13421","title":"Generalization and Memorization in Rectified Flow","created":"2026-03-12","cited_by_count":0,"area":"diffusion"},{"id":"2603.28942","title":"ReproMIA: A Comprehensive Analysis of Model Reprogramming for Proactive Membership Inference Attacks","created":"2026-03-30","cited_by_count":0,"area":"diffusion"},{"id":"2604.08037","title":"PrivFedTalk: Privacy-Aware Federated Diffusion with Identity-Stable Adapters for Personalized Talking-Head Generation","created":"2026-04-09","cited_by_count":0,"area":"diffusion"},{"id":"2605.16445","title":"Membership Inference Attacks on Discrete Diffusion Language Models","created":"2026-05-15","cited_by_count":0,"area":"diffusion"},{"id":"2606.02607","title":"Geometry-Aware Tabular Diffusion","created":"2026-05-23","cited_by_count":0,"area":"diffusion"},{"id":"2606.07640","title":"No Free Lunch for Synthetic Images under Data Scarcity Conditions","created":"2026-06-01","cited_by_count":0,"area":"diffusion"},{"id":"2607.16207","title":"JUMP: Single-Pass Membership Inference on Fine-Tuned Diffusion Language Models","created":"2026-05-09","cited_by_count":0,"area":"diffusion"},{"id":"2607.16300","title":"FedDP-PALD: A Privacy-Preserving Federated Latent Diffusion Framework with Prototype Aggregation for Medical Data Synthesis","created":"2026-07-13","cited_by_count":0,"area":"diffusion"},{"id":"2608.22824","title":"DIME: Query-Efficient Framework for Membership Inference on Diffusion Models","created":"2026-08-24","cited_by_count":0,"area":"diffusion"},{"id":"2609.10608","title":"Adaptive Diffusion Freezing: Privacy-preserving Diffusion Models Against Membership Inference Attacks","created":"2026-09-08","cited_by_count":0,"area":"diffusion"},{"id":"2610.00209","title":"Energy Time-Series Imputation with Differentially Private Diffusion Models via Clipping-Aware Objective Conditioning","created":"2026-09-21","cited_by_count":0,"area":"diffusion"},{"id":"2610.04038","title":"Protecting Sensitive Data in Image Synthesis via PAC-Private Adaptation for Diffusion Models","created":"2026-10-02","cited_by_count":0,"area":"diffusion"}],"next_cursor":null}