PPU-Bench is a real-world benchmark exposing forget-retain trade-offs in MLLM unlearning and motivating Boundary-Aware Optimization to enforce intra-subject factual boundaries.
Single image unlearning: Efficient machine unlearning in multimodal large language models.Advances in Neural Information Processing Systems, 37:35414–35453
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ICU-Bench is a new continual unlearning benchmark for MLLMs using 1000 privacy profiles, 9500 images, and 100 forget tasks, showing existing methods fail to balance forgetting, utility, and scalability.
A contrastive visual forgetting technique constrained to the null space of retained knowledge enables targeted unlearning of visual concepts in MLLMs while preserving non-target visual and all textual knowledge.
Missing-by-Design learns property-aware embeddings and uses saliency-driven Gaussian updates to produce machine-verifiable certificates that remove a chosen modality without full retraining.
citing papers explorer
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PPU-Bench:Real World Benchmark for Personalized Partial Unlearning in Vision Language Models
PPU-Bench is a real-world benchmark exposing forget-retain trade-offs in MLLM unlearning and motivating Boundary-Aware Optimization to enforce intra-subject factual boundaries.
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ICU-Bench:Benchmarking Continual Unlearning in Multimodal Large Language Models
ICU-Bench is a new continual unlearning benchmark for MLLMs using 1000 privacy profiles, 9500 images, and 100 forget tasks, showing existing methods fail to balance forgetting, utility, and scalability.
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Null Space Constrained Contrastive Visual Forgetting for MLLM Unlearning
A contrastive visual forgetting technique constrained to the null space of retained knowledge enables targeted unlearning of visual concepts in MLLMs while preserving non-target visual and all textual knowledge.
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Missing-by-Design: Certifiable Modality Deletion for Revocable Multimodal Sentiment Analysis
Missing-by-Design learns property-aware embeddings and uses saliency-driven Gaussian updates to produce machine-verifiable certificates that remove a chosen modality without full retraining.