CoME: Empowering Channel-of-Mobile-Experts with Informative Hybrid-Capabilities Reasoning
On the map: LLM agents and tool use → GUI and mobile agents
Abstract (arXiv)
Mobile Agents can autonomously execute user instructions, which requires hybrid-capabilities reasoning, including screen summary, subtask planning, action decision and action function. However, existing agents struggle to achieve both decoupled enhancement and balanced integration of these capabilities. To address these challenges, we propose Channel-of-Mobile-Experts (CoME), a novel agent architecture consisting of four distinct experts, each aligned with a specific reasoning stage, CoME activates the corresponding expert to generate output tokens in each reasoning stage via output-oriented activation. To empower CoME with hybrid-capabilities reasoning, we introduce a progressive training strategy: Expert-FT enables decoupling and enhancement of different experts' capability; Router-FT aligns expert activation with the different reasoning stage; CoT-FT facilitates seamless collaboration and balanced optimization across multiple capabilities. To mitigate error propagation in hybrid-capabilities reasoning, we propose InfoGain-Driven DPO (Info-DPO), which uses information gain to evaluate the contribution of each intermediate step, thereby guiding CoME toward more informative reasoning. Comprehensive experiments show that CoME outperforms dense mobile agents and MoE methods on both AITZ and AMEX datasets.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Placed in GUI and mobile agents, one of 16 directions in LLM agents and tool use. First posted on arXiv 27 Feb 2026.
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Citing papers per year: 2026: 5.
5 papers.
- 2026How Mobile World Model Guides GUI Agents?cited by 8
- 2026PhoneBuddy: Training Open Models for Agentic Phone Usecited by 4
- 2026AppDeltaWorld: Transition-Grounded Delta Code World Model for Mobile GUI Agentscited by 2
- 2026PhoneWorld: From Real-App Trajectories to Dynamic and Verifiable Environments for Phone-Use Agentscited by 1
- 2026BlueLM-GUI Technical Report: A Real-Device-Centric Flywheel for Self-Improving Mobile GUI Agentscited by 0
- 2026BlueLM-GUI Technical Report: A Real-Device-Centric Flywheel for Self-Improving Mobile GUI Agents11 Sep 2026
- 2026AppDeltaWorld: Transition-Grounded Delta Code World Model for Mobile GUI Agents6 Aug 2026
- 2026PhoneBuddy: Training Open Models for Agentic Phone Use22 Jun 2026
- 2026PhoneWorld: From Real-App Trajectories to Dynamic and Verifiable Environments for Phone-Use Agents28 May 2026
- 2026How Mobile World Model Guides GUI Agents?11 May 2026
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