Telecom World Models introduce a three-layer architecture for learned, action-conditioned, uncertainty-aware modeling of 6G network dynamics, combining digital twins and foundation models, with a network slicing proof-of-concept showing improved KPI prediction over baselines.
Large-scale AI in telecom: Charting the roadmap for innovation, scalability, and enhanced digital experiences
4 Pith papers cite this work. Polarity classification is still indexing.
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2026 4representative citing papers
TeleCom-Bench reveals LLMs reach 90% on telecom intent and entity tasks but drop to 30% on solution generation and root cause analysis in live network scenarios.
A hybrid beamforming framework combining liquid crystal antennas and liquid neural networks delivers 88.6% spectral efficiency gain and improved robustness in 108 GHz urban ray-tracing simulations compared to baselines and 3GPP models.
The paper envisions AI-native 6G networks anchored by a foundation model and multi-agent systems to shift network management to a unified multi-modal optimization problem.
citing papers explorer
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Telecom World Models: Unifying Digital Twins, Foundation Models, and Predictive Planning for 6G
Telecom World Models introduce a three-layer architecture for learned, action-conditioned, uncertainty-aware modeling of 6G network dynamics, combining digital twins and foundation models, with a network slicing proof-of-concept showing improved KPI prediction over baselines.
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TeleCom-Bench: How Far Are Large Language Models from Industrial Telecommunication Applications?
TeleCom-Bench reveals LLMs reach 90% on telecom intent and entity tasks but drop to 30% on solution generation and root cause analysis in live network scenarios.
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Robust Hybrid Beamforming with Liquid Crystal Antennas and Liquid Neural Networks
A hybrid beamforming framework combining liquid crystal antennas and liquid neural networks delivers 88.6% spectral efficiency gain and improved robustness in 108 GHz urban ray-tracing simulations compared to baselines and 3GPP models.
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Towards Resilient and Autonomous Networks: A BlueSky Vision on AI-Native 6G
The paper envisions AI-native 6G networks anchored by a foundation model and multi-agent systems to shift network management to a unified multi-modal optimization problem.