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.
Data traffic prediction for 5G and beyond: Emerging trends, challenges, and future directions: A scoping review
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
background 1
citation-polarity summary
fields
cs.NI 1years
2026 1verdicts
UNVERDICTED 1roles
background 1polarities
background 1representative citing papers
citing papers explorer
-
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.