AI RESEARCH
A Systematic Exploration of Text Decomposition and Budget Distribution in Differentially Private Text Obfuscation
arXiv CS.CL
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ArXi:2605.01065v1 Announce Type: new The goal of differentially private text obfuscation is to obfuscate, or "perturb", input texts with Differential Privacy (DP) guarantees, such that the private output texts are quantifiably indistinguishable from the originals. While perturbation at the word level is intuitive, meaningful text privatization happens on complete documents. Recent research has laid the groundwork for reasoning about privacy budget distribution, namely, how an overall $\varepsilon$ budget can be sensibly distributed among the component pieces of a text.