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UCA-Flow achieves a remarkable 9.3% increase in action success rates while being up to 45.6 times faster than previous approaches.
Achieving similar performance to larger models with significantly less data and faster inference speeds could redefine efficiency benchmarks in foundation models.
One model to control them all: Qwen-VLA achieves impressive zero-shot generalization across diverse robotic tasks and embodiments by unifying vision-language-action modeling.
Robots can now understand and act on your gaze while following language commands, enabling more intuitive and precise human-robot collaboration.
