mlsanityData to 7 Oct 2026

The Next Paradigm Is User-Centric Agent, Not Platform-Centric Service

arXiv 2602.15682 ↗First posted 17 Feb 2026cs.IRcited by 8

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Abstract (arXiv)

Modern digital services have evolved into indispensable tools, driving the present large-scale information systems. Yet, the prevailing platform-centric model, where services are optimized for platform-driven metrics such as engagement and conversion, often fails to align with users' true needs. While platform technologies have advanced significantly-especially with the integration of large language models (LLMs)-we argue that improvements in platform service quality do not necessarily translate to genuine user benefit. Instead, platform-centric services prioritize provider objectives over user welfare, resulting in conflicts against user interests. This paper argues that the future of digital services should shift from a platform-centric to a user-centric agent. These user-centric agents prioritize privacy, align with user-defined goals, and grant users control over their preferences and actions. With advancements in LLMs and on-device intelligence, the realization of this vision is now feasible. This paper explores the opportunities and challenges in transitioning to user-centric intelligence, presents a practical device-cloud pipeline for its implementation, and discusses the necessary governance and ecosystem structures for its adoption.

Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). First posted on arXiv 17 Feb 2026.

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Citing papers per year: 2026: 8.

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  1. 2026LLM Agents Enable User-Governed Personalization Beyond Platform Boundaries
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  3. 2026SovereignPA-Bench: Evaluating User-Owned Personal Agents under Evolving Intent, Platform Mediation, and Consent Constraints
  4. 2025Build Agent Advocates, Not Platform Agents
  5. 2026From Fragmentation to Integration: Exploring the Design Space of AI Agents for Human-as-the-Unit Privacy Management
  6. 2026PAAC: Privacy-Aware Agentic Device-Cloud Collaboration
  7. 2026DevicesWorld: Benchmarking Cross-Device Agents in Heterogeneous Environments
  8. 2026Agents That Know Too Much: A Data-Centric Survey of Privacy in LLM Agents