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Attacca: goal-directed control under state continuity for long-horizon embodied agents

AI agents
Visual goal-conditioned policies for embodied agents are almost always evaluated on isolated interactions where the target is already visible. Attacca tackles the real setting: sequences of interdependent tasks in continuous long-horizon execution, where each task starts from the state left by the previous one and the target isn't necessarily in scene. A step toward agents that accomplish complex objectives in one uninterrupted session.

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