DP-TabICL: In-Context Learning with Differentially Private Tabular Data

The author explores the use of differential privacy to protect tabular data in the context of in-context learning, proposing two frameworks - LDP-TabICL and GDP-TabICL - that offer privacy guarantees while maintaining performance.