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Small LLM agents proposed for deadline-aware V2X scheduling in 5G/6G networks

By PulseAugur Editorial · [1 sources] ·

This paper introduces Agentic-V2X, an architecture designed to use small language models for deadline-aware vehicle-to-everything (V2X) scheduling in 5G/6G networks. The system employs a small, local language model to generate policies, which are then validated and executed by a lightweight controller. Evaluations using ns-3/ns3-ai demonstrate that Agentic-V2X can produce valid policies and maintain competitive performance, particularly in critical reliability scenarios, though it does not consistently outperform the strongest static policies. AI

IMPACT Proposes a novel architecture for integrating small LLMs into real-time network scheduling, addressing latency and control concerns.

RANK_REASON Academic paper detailing a novel architecture for LLM agents in network scheduling. [lever_c_demoted from research: ic=1 ai=1.0]

Read on Hugging Face Daily Papers →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Small LLM agents proposed for deadline-aware V2X scheduling in 5G/6G networks

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Academic paper detailing a novel architecture for LLM agents in network scheduling. [lever_c_demoted from research: ic=1 ai=1.0]
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  1. Hugging Face Daily Papers TIER_1 English(EN) ·

    Agentic-V2X: Small Language Model Agents for Deadline-Aware V2X Scheduling in 5G/6G Networks

    Large Language Models (LLMs) are proposed as control interfaces for next-generation networks, but their latency, hallucinations, and lack of control guarantees make them unsuitable for near-real-time packet schedulers, especially in dynamic V2X environments. This paper introduces…

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