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When Retain Constraints Conflict: Mitigating Forget-Retain Interference in Tabular Data
Machine unlearning aims to remove the influence of designated training data while preserving model utility, but its behavior on tabular data remains underexplored. This gap is important because tabular prediction is widely used in high-stakes domains and is increasingly adapted to language models th
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