arXiv Machine Learning September 10, 2026 By Zijie Liu, Jinhao Duan, Bingqi Shang, Xinming An, Sijia Liu, Tianlong Chen

When Retain Constraints Conflict: Mitigating Forget-Retain Interference in Tabular Data

Read the original on arXiv Machine Learning →

The paper introduces Conflict-Aware Unlearning (CAU), a schema‑aware method designed to reduce forget‑retain interference in tabular data. CAU relaxes preservation constraints on retained rows that conflict most with the forget set, improving alignment with a retraining oracle while preserving predictive utility. Experiments on clinical and non‑medical tabular tasks demonstrate CAU’s effectiveness for both sample‑level and feature‑level unlearning.

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