cs.AI updates on arXiv.org 10月10日
大型语言模型应用范式分析
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本文分析了大型语言模型(LLMs)的四大应用范式:LLM应用商店、LLM代理、自托管LLM服务和LLM设备,并探讨了其架构设计、应用生态、研究进展、挑战及未来方向。

arXiv:2503.04596v2 Announce Type: replace-cross Abstract: The development of large language models (LLMs) has given rise to four major application paradigms: LLM app stores, LLM agents, self-hosted LLM services, and LLM-powered devices. Each has its advantages but also shares common challenges. LLM app stores lower the barrier to development but lead to platform lock-in; LLM agents provide autonomy but lack a unified communication mechanism; self-hosted LLM services enhance control but increase deployment complexity; and LLM-powered devices improve privacy and real-time performance but are limited by hardware. This paper reviews and analyzes these paradigms, covering architecture design, application ecosystem, research progress, as well as the challenges and open problems they face. Based on this, we outline the next frontier of LLM applications, characterizing them through three interconnected layers: infrastructure, protocol, and application. We describe their responsibilities and roles of each layer and demonstrate how to mitigate existing fragmentation limitations and improve security and scalability. Finally, we discuss key future challenges, identify opportunities such as protocol-driven cross-platform collaboration and device integration, and propose a research roadmap for openness, security, and sustainability.

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大型语言模型 应用范式 架构设计 研究进展 未来方向
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