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StateVLM: A State-Aware Vision-Language Model for Robotic Affordance Reasoning
Vision-language models have demonstrated strong performance across robotic perception and instruction-following tasks. However, they still struggle with precise spatial reasoning, particularly in predicting object locations and fine-grained object states. We propose StateVLM, a vision-language model
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