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Achieve robust robot manipulation across diverse viewpoints without camera calibration by synthesizing novel views with a geometry-aware video diffusion model.
Pocket-sized VLA models can now achieve state-of-the-art robot manipulation performance by pre-training on a curated multimodal dataset and injecting manipulation-relevant representations into the action space.
End-to-end driving models are surprisingly bad at using navigation, but a new framework shows how to inject it for SOTA results.
LLMs can now write better hardware verification code: CoverAssert boosts functional coverage by up to 15% by iteratively guiding LLMs with coverage feedback.
