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Gripper-aware models can dramatically improve robotic manipulation by tailoring strategies to specific gripper types, leading to better performance in diverse tasks.
SC3-Eval achieves a remarkable 0.929 Pearson correlation in evaluating robot policies, revealing critical insights into their real-world performance.
Robots can now remember what they've done and what they need to do next for 15 minutes straight, thanks to a new memory architecture that mixes video and text.
