Where Identity Lives: Localized, Retain-Free Identity Unlearning in Multimodal Large Language Models

arXiv:2608.30649 · cs.CL, cs.CV · Submitted 2026-08-31 · Read on arXiv

cs.CL, cs.CV

Submitted: 2026-08-31

Updated: 2026-08-31

Terminology

• Grounding — 10× in this paper · explained in 3 episodes
• Benchmark — 8× in this paper · explained in 2 episodes
• Trace — 8× in this paper · explained in 2 episodes
• Machine Unlearning — 7× in this paper · explained in 2 episodes
• Transformer — 5× in this paper · explained in 2 episodes
• Visual-Attribute Anchor — 4× in this paper
• Ablation — 3× in this paper · explained in 1 episode
• Accuracy — 3× in this paper · explained in 1 episode
• Generalization — 3× in this paper · explained in 13 episodes
• Fine-Tuning — 2× in this paper · explained in 5 episodes
• Instruction Tuning — 2× in this paper · explained in 2 episodes
• Pruning — 2× in this paper · explained in 4 episodes
• Visual Grounding — 2× in this paper · explained in 2 episodes
• Activation Patching — 1× in this paper · explained in 2 episodes
• Adaptation — 1× in this paper · explained in 1 episode
• Aggregation — 1× in this paper · explained in 1 episode
• Catastrophic Forgetting — 1× in this paper · explained in 5 episodes
• Core — 1× in this paper · explained in 2 episodes
• Digital Twin — 1× in this paper · explained in 4 episodes
• Failure Modes — 1× in this paper · explained in 3 episodes
• Fisher Information — 1× in this paper · explained in 3 episodes
• Hallucination — 1× in this paper · explained in 3 episodes
• Hallucination Mitigation — 1× in this paper · explained in 2 episodes
• Interpretability — 1× in this paper · explained in 15 episodes
• LoRA Adapters — 1× in this paper · explained in 3 episodes
• LoRA Fine-Tuning — 1× in this paper · explained in 3 episodes
• Pathway-Aware Visualattribute Anchoring — 1× in this paper
• Regularization — 1× in this paper · explained in 3 episodes

Sources

• Qwen3-VL Technical Report
• Qwen2.5-VL Technical Report
• Visual-Guided Key-Token Regularization for Multimodal Large Language Model Unlearning
• Knowledge Vector Weakening: Efficient Training-free Unlearning for Large Vision-Language Models

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