{"total":40,"rows":[{"id":"2110.05679","title":"Large Language Models Can Be Strong Differentially Private Learners","created":"2021-10-12","cited_by_count":412,"area":null},{"id":"2302.04062","title":"Machine Learning for Synthetic Data Generation: A Review","created":"2023-02-08","cited_by_count":120,"area":null},{"id":"2204.00401","title":"CTAB-GAN+: Enhancing Tabular Data Synthesis","created":"2022-04-01","cited_by_count":70,"area":null},{"id":"2306.01684","title":"Harnessing large-language models to generate private synthetic text","created":"2023-06-02","cited_by_count":65,"area":null},{"id":"2401.06091","title":"A Closer Look at AUROC and AUPRC under Class Imbalance","created":"2024-01-11","cited_by_count":57,"area":null},{"id":"2307.02106","title":"SoK: Privacy-Preserving Data Synthesis","created":"2023-07-05","cited_by_count":38,"area":null},{"id":"2305.11567","title":"TSGM: A Flexible Framework for Generative Modeling of Synthetic Time Series","created":"2023-05-19","cited_by_count":18,"area":null},{"id":"2401.13716","title":"Can I trust my fake data -- A comprehensive quality assessment framework for synthetic tabular data in healthcare","created":"2024-01-24","cited_by_count":17,"area":null},{"id":"2204.04797","title":"Multi-Label Clinical Time-Series Generation via Conditional GAN","created":"2022-04-10","cited_by_count":16,"area":null},{"id":"2107.09543","title":"Data synthesis and adversarial networks: A review and meta-analysis in cancer imaging","created":"2021-07-20","cited_by_count":15,"area":null},{"id":"2211.11591","title":"DPD-fVAE: Synthetic Data Generation Using Federated Variational Autoencoders With Differentially-Private Decoder","created":"2022-11-21","cited_by_count":14,"area":null},{"id":"2309.16398","title":"Recent Advances of Differential Privacy in Centralized Deep Learning: A Systematic Survey","created":"2023-09-28","cited_by_count":12,"area":null},{"id":"2205.08886","title":"GeoPointGAN: Synthetic Spatial Data with Local Label Differential Privacy","created":"2022-05-18","cited_by_count":9,"area":null},{"id":"2410.21717","title":"Generating Realistic Tabular Data with Large Language Models","created":"2024-10-29","cited_by_count":9,"area":null},{"id":"2411.00024","title":"A Perspective for Adapting Generalist AI to Specialized Medical AI Applications and Their Challenges","created":"2024-10-28","cited_by_count":8,"area":null},{"id":"2107.02521","title":"DTGAN: Differential Private Training for Tabular GANs","created":"2021-07-06","cited_by_count":7,"area":null},{"id":"2307.15424","title":"Deep Generative Models, Synthetic Tabular Data, and Differential Privacy: An Overview and Synthesis","created":"2023-07-28","cited_by_count":7,"area":null},{"id":"2506.00660","title":"Differential privacy for medical deep learning: methods, tradeoffs, and deployment implications","created":"2025-05-31","cited_by_count":7,"area":null},{"id":"2308.14784","title":"Generating tabular datasets under differential privacy","created":"2023-08-28","cited_by_count":6,"area":null},{"id":"2411.03351","title":"Tabular Data Synthesis with Differential Privacy: A Survey","created":"2024-11-04","cited_by_count":6,"area":null},{"id":"2307.07047","title":"Does Collaborative Human-LM Dialogue Generation Help Information Extraction from Human Dialogues?","created":"2023-07-13","cited_by_count":5,"area":null},{"id":"2402.14042","title":"Protect and Extend -- Using GANs for Synthetic Data Generation of Time-Series Medical Records","created":"2024-02-21","cited_by_count":4,"area":null},{"id":"2510.18768","title":"Improving the Generation and Evaluation of Synthetic Data for Downstream Medical Causal Inference","created":"2025-10-21","cited_by_count":4,"area":null},{"id":"2206.13787","title":"Improving Correlation Capture in Generating Imbalanced Data using Differentially Private Conditional GANs","created":"2022-06-28","cited_by_count":3,"area":null},{"id":"2306.00687","title":"Adversarial Robustness in Unsupervised Machine Learning: A Systematic Review","created":"2023-06-01","cited_by_count":3,"area":null},{"id":"2311.06118","title":"Exploring the Efficacy of Base Data Augmentation Methods in Deep Learning-Based Radiograph Classification of Knee Joint Osteoarthritis","created":"2023-11-10","cited_by_count":3,"area":null},{"id":"2312.15187","title":"IRG: Modular Synthetic Relational Database Generation with Complex Relational Schemas","created":"2023-12-23","cited_by_count":3,"area":null},{"id":"2108.10064","title":"Effective and Privacy preserving Tabular Data Synthesizing","created":"2021-08-11","cited_by_count":2,"area":null},{"id":"2303.01621","title":"GlucoSynth: Generating Differentially-Private Synthetic Glucose Traces","created":"2023-03-02","cited_by_count":2,"area":null},{"id":"2502.13193","title":"Private Text Generation by Seeding Large Language Model Prompts","created":"2025-02-18","cited_by_count":2,"area":null},{"id":"2203.04462","title":"Downstream Fairness Caveats with Synthetic Healthcare Data","created":"2022-03-09","cited_by_count":1,"area":null},{"id":"2309.12380","title":"Methods for generating and evaluating synthetic longitudinal patient data: a systematic review","created":"2023-09-21","cited_by_count":1,"area":null},{"id":"2311.05798","title":"Synthesizing Bidirectional Temporal States of Knee Osteoarthritis Radiographs with Cycle-Consistent Generative Adversarial Neural Networks","created":"2023-11-10","cited_by_count":1,"area":null},{"id":"2311.05799","title":"Adaptive Variance Thresholding: A Novel Approach to Improve Existing Deep Transfer Vision Models and Advance Automatic Knee-Joint Osteoarthritis Classification","created":"2023-11-10","cited_by_count":1,"area":null},{"id":"2404.00696","title":"Privacy Re-identification Attacks on Tabular GANs","created":"2024-03-31","cited_by_count":1,"area":null},{"id":"2506.23358","title":"Federated Timeline Synthesis: Scalable and Private Methodology For Model Training and Deployment","created":"2025-06-29","cited_by_count":1,"area":null},{"id":"2304.01108","title":"Coincidental Generation","created":"2023-04-03","cited_by_count":0,"area":null},{"id":"2404.16913","title":"DE-CGAN: Boosting rTMS Treatment Prediction with Diversity Enhancing Conditional Generative Adversarial Networks","created":"2024-04-25","cited_by_count":0,"area":null},{"id":"2506.16661","title":"Private Training & Data Generation by Clustering Embeddings","created":"2025-06-20","cited_by_count":0,"area":null},{"id":"2602.09288","title":"Measuring Privacy Risks and Tradeoffs in Financial Synthetic Data Generation","created":"2026-02-10","cited_by_count":0,"area":null}],"next_cursor":null}