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Zeekr, Geely Auto
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Executable visual transformations enable MLLMs to achieve continuous self-evolution without the pitfalls of pseudo-labels, leading to superior performance in dynamic VQA tasks.
LLMs can now generate complex, physically plausible 3D scenes for robotics simulation by iteratively proposing assets and refining arrangements based on physics engine feedback.
