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Image generation models exhibit a surprising "Order-to-Space Bias," meaning the order you mention objects in a prompt can drastically alter their placement in the generated image, even overriding other visual cues.
Training a single point cloud encoder across diverse 3D domains not only improves perception but also unlocks emergent behaviors and enhances robotic manipulation and spatial reasoning.
AI-generated images betray themselves not by their appearance, but by their *behavior*: they are far more sensitive to small perturbations than real images, revealing a fundamental weakness exploitable for universal detection.
