mlsanityData to 14 Oct 2026

Tele-LLM-Hub: Building Context-Aware Multi-Agent LLM Systems for Telecom Networks

arXiv 2511.09087 ↗First posted 12 Nov 2025cs.NI cs.AIcited by 2

On the map: LLM agents and tool use → Agentic AI for wireless networks

Abstract (arXiv)

This paper introduces Tele-LLM-Hub, a user friendly low-code solution for rapid prototyping and deployment of context aware multi-agent (MA) Large Language Model (LLM) systems tailored for 5G and beyond. As telecom wireless networks become increasingly complex, intelligent LLM applications must share a domainspecific understanding of network state. We propose TeleMCP, the Telecom Model Context Protocol, to enable structured and context-rich communication between agents in telecom environments. Tele-LLM-Hub actualizes TeleMCP through a low-code interface that supports agent creation, workflow composition, and interaction with software stacks such as srsRAN. Key components include a direct chat interface, a repository of pre-built systems, an Agent Maker leveraging finetuning with our RANSTRUCT framework, and an MA-Maker for composing MA workflows. The goal of Tele-LLM-Hub is to democratize the design of contextaware MA systems and accelerate innovation in next-generation wireless networks.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Placed in Agentic AI for wireless networks, one of 16 directions in LLM agents and tool use. First posted on arXiv 12 Nov 2025.

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 2.

2 papers.

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  7. 2025Survey of LLM Agent Communication with MCP: A Software Design Pattern Centric Review
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