
Large language models like GPT-4 can be effectively leveraged to sanitize tabular data in a way that hinders the extraction of sensitive user information while retaining the ability to extract useful features.


coremsg

leveraging-gpt-4-for-privacy-preserving-sanitization-of-tabular-data


Leveraging GPT-4 for Privacy-Preserving Sanitization of Tabular Data


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This paper introduces Balanced and Entropy-based Mix (BEM), a novel data mixing approach that re-balances both the class distribution of data quantity and uncertainty to enhance long-tailed semi-supervised learning.


balanced-and-entropy-based-mixing-for-enhancing-long-tailed-semi-supervised-learning


Balanced and Entropy-based Mixing for Enhancing Long-Tailed Semi-Supervised Learning
