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SIEVE: Selective attention-value Suppression for Vision-Language Models Unlearning
The ability of vision-language models (VLMs) to associate visual identities with biographical information creates a need for selective unlearning of personally identifiable information (PII) while preserving permitted knowledge about the same individual. This setting is challenging because both sens
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