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Cognitive AI Systems Lab, MIRAI
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ARMT-augmented models can handle inputs far beyond their original context limits while using 30% less compute, revolutionizing efficiency in long-context processing.
Isolating recurrence in VLA models reveals it can double success rates in partially observable tasks without complicating architecture or introducing auxiliary losses.
