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📄 ResearchJune 15, 2026

Phantoms and Disclosures: a Causal Framework for Auditing Synthetic Data

The rapid adoption of generative AI and Large Language Models (LLMs) has spurred interest in synthetic data as a privacy-preserving alternative to sensitive real-world datasets. However, generating high-utility synthetic data often carries the risk of memorizing and regurgitating private information...

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Source

http://arxiv.org/abs/2606.16952v1