ClawMobile: Rethinking Smartphone-Native Agentic Systems
Du, Hongchao Wu, Shangyu Li, Qiao Pan, Riwei Li, Jinheng Sun, Youcheng Xue, Chun Jason
Du, Hongchao
Wu, Shangyu
Li, Qiao
Pan, Riwei
Li, Jinheng
Sun, Youcheng
Xue, Chun Jason
Supervisor
Department
Computer Science
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Conference proceeding
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Language
English
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Abstract
Smartphones represent a uniquely challenging environment for agentic systems. Unlike cloud or desktop settings, mobile devices combine constrained execution contexts, fragmented control interfaces, and rapidly changing application states. As large language models (LLMs) evolve from conversational assistants to action-oriented agents, achieving reliable smartphone-native autonomy requires rethinking how reasoning and control are composed. We introduce ClawMobile as a concrete exploration of this design space. ClawMobile adopts a hierarchical architecture that separates high-level language reasoning from structured, deterministic control pathways, improving execution stability and reproducibility on real devices. Using ClawMobile as a case study, we distill the design principles for mobile LLM runtimes and identify key challenges in efficiency, adaptability, and stability. We argue that building robust smartphone-native agentic systems demands principled coordination between probabilistic planning and deterministic system interfaces. The implementation is open-sourced 1 to facilitate future exploration.
Citation
H. Du, S. Wu, Q. Li, R. Pan, J. Li, Y. Sun , et al., "ClawMobile: Rethinking Smartphone-Native Agentic Systems," 2026, pp. 370-376.
Source
EuroMLSys '26: Proceedings of the Sixth European Workshop on Machine Learning and Systems
Conference
Proceedings of the Sixth European Workshop on Machine Learning and Systems
Keywords
46 Information and Computing Sciences, 4602 Artificial Intelligence
Subjects
Source
Proceedings of the Sixth European Workshop on Machine Learning and Systems
Publisher
Association for Computing Machinery