TSQAgent: Rating Time Series Data Quality via Dedicated Agentic Reasoning 事件

TSQAgent: Rating Time Series Data Quality via Dedicated Agentic Reasoning arXiv:2606.03629v1 Announce Type: new Abstract: Assessing the quality of time series (TS) data is fundamental yet inherently challenging due to the multifaceted nature of quality dimensions. Recently, large language models (LLMs) have emerged as a promising paradigm for TS quality assessment via pairwise comparison and per-dimension evaluation. However, existing approaches rely on manually predefined quality dimensions an