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CoME: Empowering Channel-of-Mobile-Experts with Informative Hybrid-Capabilities Reasoning
arXiv – CS AI|Yuxuan Liu, Weikai Xu, Kun Huang, Changyu Chen, Jiankun Zhao, Pengzhi Gao, Wei Liu, Jian Luan, Shuo Shang, Bo Du, Ji-Rong Wen, Rui Yan||8 views
🤖AI Summary
Researchers introduce Channel-of-Mobile-Experts (CoME), a new AI agent architecture that uses four specialized experts to handle different reasoning stages for mobile device automation. The system employs progressive training strategies and information gain-driven optimization to improve mobile agent performance on complex tasks.
Key Takeaways
- →CoME introduces a novel mobile agent architecture with four distinct experts handling screen summary, subtask planning, action decision, and action function.
- →The system uses output-oriented activation to selectively engage appropriate experts for different reasoning stages.
- →Progressive training strategy includes Expert-FT, Router-FT, and CoT-FT phases to enhance capabilities and coordination.
- →Info-DPO method uses information gain to evaluate intermediate steps and reduce error propagation in reasoning.
- →Experimental results show CoME outperforms existing dense mobile agents and MoE methods on AITZ and AMEX datasets.
#mobile-agents#ai-architecture#machine-learning#automation#expert-systems#reasoning#training-methods#performance-optimization
Read Original →via arXiv – CS AI
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