most citedDifferentially Private Aggregation in the Shuffle Model: Almost Central Accuracy in Almost a Single Message

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cs.LG2025

Scaling Laws for Differentially Private Language Models

Ryan McKenna, Yangsibo Huang, Amer Sinha +9

Scaling laws have emerged as important components of large language model (LLM) training as they can predict performance gains through scale, and provide guidance on important hype…