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Harbin Institute of Technology, Shenzhen
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Non-thinking inference in hybrid-thinking MLLMs suffers from a staggering increase in response-pattern failures, revealing a critical misalignment that can undermine user trust.
Mobile agents can now navigate complex GUIs with unprecedented efficiency, thanks to a novel data-environment co-scaling framework.
Achieving a 6.37x speedup in inference while expanding OCR capabilities across long-tail tasks sets a new benchmark for lightweight models.
Task success rates for agentic phone use soar from 36.67% to 45.33% through a novel combination of real and mock environments in training.
Reliable phone automation hinges on mixed-action capabilities, with agents achieving a 75% success rate in real-world workflows.
ChartArena reveals that even top proprietary models struggle with diagrammatic structures, exposing critical gaps in current chart parsing capabilities.
Forget hand-crafting mobile benchmarks – PhoneWorld lets you automatically generate them from real-world GUI trajectories, leading to massive performance gains for phone-use agents.
