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Embodied agents can now reliably achieve complex, multi-stage goals in dynamic environments by learning to predict and ground targets from decoupled visual context, even when the goal is out of view.
MLLMs struggle with artistic intent, scoring only 48.29% on a benchmark designed to evaluate nuanced understanding in audiovisual arts.
