arxiv
PublishedJuly 14, 2026 at 4:00 AM
Private Seeds, Public LLMs: Realistic and Privacy-Preserving Synthetic Data Generation
Publisher summary· verbatim
arXiv:2604.07486v3 Announce Type: replace-cross Abstract: Large language models (LLMs) have emerged as a powerful tool for synthetic data generation. A particularly important use case is producing synthetic replicas of private text, which requires carefully balancing privacy and utility. We propose
Stay posted· Newsletter
A 5-min weekly brief — top movers, price watch, story of the week.
Discussion
No replies yet. Be first.
Related coverage
More from ARXIV
arxivIMEX Interaction-Based Model Explanation1harxivDialogueVPR: Towards Conversational Visual Place Recognition1harxivHuman AI Construction of Bayesian Networks for Operational Decision Support -- A Virtual Survey Approach1harxivOrchestrating Power Grid Studies with Multi-Agent AI and MCP Servers1hThe Bubble Brief
WEEKLYRead AI insights every Tuesday — top movers, new releases, story of the week.
Originally published on arxiv ↗