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The preprint studies local serving of smartphone graphical-interface agents using hybrid linear-attention models on mobile neural processing units. Such agents repeatedly inspect a screen and choose an action, so inference delay can accumulate across steps.

The work focuses on efficient recurrent-state reuse and checkpointing on mobile hardware. It presents a systems study rather than a commercial phone feature or a general claim about all mobile NPUs.