A two-stage reinforcement learning system on pretrained LLMs aligns channel state information with user intents to generate adaptive, physically realizable link construction strategies for 6G that outperform conventional methods in experiments.
LLM4CP: Adapting large language models for channel prediction,
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AI and terahertz networks form a mutual symbiosis where each addresses the limitations of the other across hardware, physical layer, protocols, and services.
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Agentic Link Construction for Environment and Intent Aware 6G Communication
A two-stage reinforcement learning system on pretrained LLMs aligns channel state information with user intents to generate adaptive, physically realizable link construction strategies for 6G that outperform conventional methods in experiments.
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When AI Meets Terahertz: A Survey on the Symbiosis of Artificial Intelligence and Terahertz Networks
AI and terahertz networks form a mutual symbiosis where each addresses the limitations of the other across hardware, physical layer, protocols, and services.