mlsanityData to 13 Oct 2026

LLM for Mobile: An Initial Roadmap

arXiv 2407.06573 ↗First posted 9 Jul 2024cs.SEcited by 11

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Abstract (arXiv)

When mobile meets LLMs, mobile app users deserve to have more intelligent usage experiences. For this to happen, we argue that there is a strong need to appl LLMs for the mobile ecosystem. We therefore provide a research roadmap for guiding our fellow researchers to achieve that as a whole. In this roadmap, we sum up six directions that we believe are urgently required for research to enable native intelligence in mobile devices. In each direction, we further summarize the current research progress and the gaps that still need to be filled by our fellow researchers.

Key facts. Cited by 11 papers in the map (data through 13 Oct 2026). First posted on arXiv 9 Jul 2024.

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Cited by year (2026 to 13 Oct)

Citing papers per year: 2024: 1; 2025: 6; 2026: 4.

11 papers.

  1. 2024Large Language Model-Brained GUI Agents: A Surveycited by 161
  2. 2026Taming Various Privilege Escalation in LLM-Based Agent Systems: A Mandatory Access Control Frameworkcited by 52
  3. 2025Measuring and Augmenting Large Language Models for Solving Capture-the-Flag Challengescited by 14
  4. 2025A Survey on Collaborative Mechanisms Between Large and Small Language Modelscited by 13
  5. 2025LaSM: Layer-wise Scaling Mechanism for Defending Pop-up Attack on GUI Agentscited by 6
  6. 2025DiSCo: Device-Server Collaborative LLM-Based Text Streaming Servicescited by 2
  7. 2025Recursive Offloading for LLM Serving in Multi-tier Networkscited by 2
  8. 2025LLM in the Middle: A Systematic Review of Threats and Mitigations to Real-World LLM-based Systemscited by 1
  9. 2026Towards Resilient and Autonomous Networks: A BlueSky Vision on AI-Native 6Gcited by 1
  10. 2026On Emotion-Sensitive Decision Making of Small Language Model Agentscited by 0
  11. 2026mzCache: On-Device LLM Memory Management under Multitaskingcited by 0