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StreamTTT outperforms existing streaming VLMs by enhancing real-time perception and long-term memory without sacrificing performance.
MANGO-Grasp achieves a remarkable 16.57 percentage point boost in zero-shot grasping performance across diverse robotic hands by leveraging geometry-oriented 3D Gaussian representations.
Explicitly structuring trajectory priors with Hermite curves can elevate robotic manipulation success rates by nearly 30%, transforming how VLA models handle action execution.
