LLaTiSA: Towards Difficulty-Stratified Time Series Reasoning from Visual Perception to Semantics

ArXi:2604.17295v1 Announce Type: new Comprehensive understanding of time series remains a significant challenge for Large Language Models (LLMs). Current research is hindered by fragmented task definitions and benchmarks with inherent ambiguities, precluding rigorous evaluation and the development of unified Time Series Reasoning Models(TSRMs). To bridge this gap, we formalize Time Series Reasoning (TSR) via a four-level taxonomy of increasing cognitive complexity. We