Rating Quality of Diverse Time Series Data by Meta-learning from LLM Judgment

ArXi:2506.01290v2 Announce Type: replace-cross High-quality time series (TS) data are essential for ensuring TS model performance, rendering research on rating TS data quality indispensable. Existing methods have shown promising rating accuracy within individual domains, primarily by extending data quality rating techniques such as influence functions and Shapley values to account for temporal characteristics.