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GigaBrain-0.7 achieves unprecedented task adaptability and completion rates, outperforming previous models in both home and industrial settings.
ST-Omni-R1 not only excels in sound-event recognition but also sets a new standard for spatial audio reasoning, achieving nearly double the accuracy of existing models.
Recursive self-improvement in Macaron-V1 leads to continual learning that adapts to real-world experiences, setting a new standard for open agent models.
Zero-robot post-training on high-fidelity UMI data achieves real-world performance that rivals traditional teleoperation methods, revolutionizing data efficiency in robotic manipulation.
Legato makes action-chunked VLA policies smoother and faster by learning a native continuation that eliminates the discontinuities introduced by chunking.
