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Coco Matrix releases robot model CO01
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Coco Matrix (COCO Matrix) has released the robot model CO01, which uses demonstrations, failed attempts, and real-time guidance as experiential prompts in context, enabling the robot to adapt to new tasks without updating weights. According to Coco Matrix, under the same pretrained model, a demonstration of about 1 minute achieves an average success rate of 52% on unseen tasks; fine-tuning to reach a comparable level requires about 180 demonstrations and about 9 hours. In real-robot evaluations, with at most five attempts per task, the cumulative success rate rose from 33% on the first attempt to 84% when retaining its own history, versus 56% without retaining history. Currently, new skills are mainly adapted through in-context learning, and cross-task preferences are stored by System 2.
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- COCO Matrix releases robot model CO01, using experience prompts to let robots learn while doing
COCO Matrix released the robot model CO01, which treats demonstrations, failed attempts, and real-time guidance as experience prompts in context, allowing adaptation to new tasks without updating weights. Under the same pretrained model, a roughly 1-minute demonstration achieved an average success rate of 52% on unseen tasks; fine-tuning to a similar level required about 180 demonstrations and about 9 hours. In real-robot evaluations with at most five attempts per task, cumulative success rate rose from 33% on the first attempt to 84% when retaining its own history, versus 56% without retaining history.
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