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Achieving 100% task success in closed-loop execution, Embodied.cpp revolutionizes how embodied AI models are deployed across diverse hardware platforms.
ActProbe predicts robot policy failures before they become visually apparent, enhancing both detection accuracy and operational efficiency in real-world tasks.
Novelty-driven interaction enables agents to explore more effectively while using memory efficiently, outperforming traditional methods in open-ended environments.
Proactive VideoLLMs can finally be both accurate AND efficient thanks to a novel propose-match framework that decouples semantic understanding from streaming perception.
