Chain-of-thought reasoning with plan-based demonstrations and similarity retrieval improves LLM mobile traffic prediction accuracy by up to 15% over standard in-context learning on real 5G data.
Rl meets multi-link operation in ieee 802.11be: Multi-headed recurrent soft-actor critic-based traffic allocation
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Chain-of-Thought Reasoning Enhances In-Context Learning for LLM-Based Mobile Traffic Prediction
Chain-of-thought reasoning with plan-based demonstrations and similarity retrieval improves LLM mobile traffic prediction accuracy by up to 15% over standard in-context learning on real 5G data.