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.
Toward agentic ai: Generative information retrieval inspired intelligent communications and networking
6 Pith papers cite this work. Polarity classification is still indexing.
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Agentic AI enables coverless semantic steganography without private keys or cover images, delivering higher capacity and security than prior schemes in semantic communication.
A framework applies generative diffusion models to predict implicit user intents and proactively orchestrate edge service function chains.
An intention-aware semantic agent system for AI glasses reduces bandwidth by over 50% in simulations while preserving task performance through adaptive preprocessing guided by inferred user intentions.
Randomized Weibull anchors and debiased collective memory with decay and inflection bonuses let agentic AI in 6G cut anchoring, temporal, and confirmation biases, doubling energy savings to 25% and reducing latency by 5x in simulations.
The paper surveys energy efficiency strategies for Agentic AI inference by proposing a new accounting framework and taxonomy that spans model simplification, computation control, input optimization, and cross-layer co-design with wireless networks.
citing papers explorer
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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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Secure Intellicise Wireless Network: Agentic AI for Coverless Semantic Steganography Communication
Agentic AI enables coverless semantic steganography without private keys or cover images, delivering higher capacity and security than prior schemes in semantic communication.
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Generative Intent Prediction Agentic AI empowered Edge Service Function Chain Orchestration
A framework applies generative diffusion models to predict implicit user intents and proactively orchestrate edge service function chains.
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Intention-Aware Semantic Agent Communications for AI Glasses
An intention-aware semantic agent system for AI glasses reduces bandwidth by over 50% in simulations while preserving task performance through adaptive preprocessing guided by inferred user intentions.
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A Tutorial on Cognitive Biases in Agentic AI-Driven 6G Autonomous Networks
Randomized Weibull anchors and debiased collective memory with decay and inflection bonuses let agentic AI in 6G cut anchoring, temporal, and confirmation biases, doubling energy savings to 25% and reducing latency by 5x in simulations.
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Networking-Aware Energy Efficiency in Agentic AI Inference: A Survey
The paper surveys energy efficiency strategies for Agentic AI inference by proposing a new accounting framework and taxonomy that spans model simplification, computation control, input optimization, and cross-layer co-design with wireless networks.