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WAVE-Go, an image-goal navigation framework that separates world-action prediction from interruptible command execution, and its executor adaptively selects an action prefix and cancels pending commands when updated observations invalidate execution, support adaptive, interruptible execution as a means of balancing navigation performance and planning overhead.
Achieving data-dependent regret bounds in policy optimization with unknown transitions could redefine our understanding of adaptive learning in MDPs.
Mem-World's innovative memory architecture boosts robot manipulation success rates from 58% to 72% on complex tasks by effectively anchoring historical observations to dynamic scene elements.
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