An LLM-guided evolutionary feature engineering method for time-series forecasting reduces RMSE by 8.4% on average across seven datasets.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
ELATE: Evolutionary Language model for Automated Time-series Engineering
An LLM-guided evolutionary feature engineering method for time-series forecasting reduces RMSE by 8.4% on average across seven datasets.