Memory-Coupled Unlearning for Data-Absent Identity Forgetting

Reported by arXiv cs.CR (Chun-I Fan, Lu-En Chen, Ming-Feng Tsai, Tomohiro Morikawa)

Summary by Cyber Security News14 Oct 2026, 06:00 CET

About this summary. This is a short excerpt from the description that arXiv cs.CR published with its article. Cyber Security News did not report or verify the underlying story. Read the original: https://arxiv.org/abs/2610.14148

arXiv:2610.14148v1 Announce Type: new Abstract: Machine unlearning aims to reduce the influence of designated training data from a trained model while preserving its utility on retained data. Identity-level unlearning is particularly challenging when only limited target-specific information is available when a forgetting request is processed.

Read the full article at arXiv cs.CR →

Source attribution: headline and facts are from arXiv cs.CR (arxiv.org). Summary method: excerpt of the source description. See our source attribution policy.

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