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Sparse Feature Policy Unlearning Mitigates State Hallucination in Vision-Language-Action Models
Vision-Language-Action (VLA) models have shown strong generalization in robotic manipulation by leveraging rich representations from pretrained vision-language models. However, their deployment in real-world environments remains limited by recurring unreliable behaviors. In this work, we study state
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