Artificial Intelligence #semantics#retrieval augmented
New AI Framework SERAF Combines Semantic and Numerical Data for Better Time Series Forecasting
Researchers propose SERAF, a semantics-enhanced retrieval-augmented time series forecasting framework that combines numerical similarity with textual descriptions to improve predictions under non-stationarity. The approach outperforms state-of-the-art baselines across seven real-world datasets.
Jun 16, 2026 1 source