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VLM-IE3D achieves state-of-the-art performance in 3D tasks by seamlessly integrating implicit and explicit geometric representations from RGB inputs.
RynnBrain 1.1 not only outperforms all competitors in embodied cognition tasks but also redefines how robots can be trained for complex manipulation through innovative 3D grounding techniques.
Robots can now autonomously adapt to camera changes without needing explicit calibration, significantly improving deployment flexibility.
RL fine-tuning LMMs for tool use can collapse structural formats due to strong pretrained tool priors, but a surprisingly simple fix of targeted format rewards and frame-budget randomization can restore stability and boost performance.
Today's visual generation models are often evaluated on the wrong things, leading to inflated performance claims that mask critical failures in spatial reasoning, temporal consistency, and causal understanding.
