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FolDeX: A Physical-World Benchmark for Long-Horizon Robotic Manipulation of Deformable Objects
Embodied AI, including vision-language-action and world-action models, must operate reliably in the physical world. Yet methods that perform well in simulation can degrade substantially on real robots, especially in long-horizon deformable-object manipulation, where policies must track changing stat
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