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cs.CR2026
Memory-Coupled Unlearning for Data-Absent Identity Forgetting
Chun-I Fan, Lu-En Chen, Ming-Feng Tsai +1
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 particu…
cs.CR2026
Don't Trust the AI Ecosystem: Analyzing Privacy Leakage in Compromised Open-Source Components
Jin-Seong Kim, Han-Ju Lee, Seok-Won Hong +4
Existing model inversion (MI) attacks predominantly rely on post-training optimization to recover private data from model outputs. However, these methods are fundamentally constrai…