Author

Evžen Wybitul

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#machine learning Preprint Sep 2026

Entangled Representations Amplify Collateral Damage in Unlearning

By repurposing Selective Gradient Masking, a suite of six 254M-parameter language models on English Wikipedia with graded levels of disentanglement between biology and non-biology knowledge are trained, it is found that more disentangled models consistently achieve better retain-forget trade-offs.

Evžen Wybitul, Tim G. J. Rudner, C. D. de Witt · 0 citations