AI RESEARCH
Look Twice before You Leap: A Rational Framework for Localized Adversarial Anonymization
arXiv CS.CL
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ArXi:2512.06713v3 Announce Type: replace-cross Current LLM-based frameworks for text anonymization usually rely on remote API services from powerful LLMs, which creates an inherent privacy paradox: users must disclose the raw data to untrusted third parties for guaranteed privacy preservation. Moreover, directly migrating current solutions to local small-scale models (LSMs) offers a suboptimal solution with severe utility collapse.