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Current VLMs struggle with multi-hop spatial reasoning, often failing to compose even simple spatial relations across multiple steps, highlighting a critical gap for real-world VLA agent deployment.
Current AI models fall short when asked to understand a situation from the combined perspectives of multiple embodied agents, as revealed by a new challenging benchmark.
