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UI-MOPD achieves a remarkable balance between retaining existing capabilities and adapting to new platforms, with task success rates that challenge conventional approaches in GUI agent learning.
Explicitly modeling rare extreme events in time series forecasting can significantly enhance predictive accuracy, as shown by Exformer's superior performance over traditional models.
Real-world GUI agents can achieve over 72% success in complex mobile tasks by leveraging a unique hybrid training approach that integrates real-device execution and adaptive learning from failures.
