Zhenbo Luo

The MaP is proposed, a unified framework that seamlessly harmonizes divergent GUI navigation tasks and effectively mitigates gradient conflicts and significantly outperforms the direct mixture training, establishing a robust paradigm for multi-task GUI navigation.

SIEVE retains 97.5% of performance while reducing visual token usage to just 11.1%, revolutionizing efficiency in vision-language models.