C law M obile : Rethinking Smartphone-Native Agentic Systems

Proceedings of the Sixth European Workshop on Machine Learning and Systems 2026 Open access

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Authors: Hongchao Du, Shangyu Wu, Qiao Li, Riwei Pan, Jinheng Li, Youcheng Sun, Chun Jason Xue
DOI: 10.1145/3805621.3807655
Cited by: 1
References: 25

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.

Fields of Study & Subjects

Multi-Agent Systems and Negotiation Advanced Software Engineering Methodologies Software System Performance and Reliability

Publication details

Journal / source
Proceedings of the Sixth European Workshop on Machine Learning and Systems
Publisher
ACM
Pages
370–376
Publication date
27 April 2026
Language
EN