From Recognition to Understanding: Unlocking Cognitive Time Series Reasoning with LLMs
Time series analysis has recently been coupled with Large Language Models (LLMs) to leverage their reasoning and world knowledge capabilities, yet gains remain limited. We attribute this to a fundamental mismatch between existing task formulations and LLM strengths: most settings reduce time series understanding to curve-fitting systems, focusing on low-level prediction while ignoring the semantic, contextual, and reasoning-intensive nature of real-world temporal decision-making.To address these limitations, we introduce TSCognition, a multimodal benchmark for multi-dimensional time series reasoning. It collects real-world time series and textual information from 15 public sources and con...
| Authors | Xin Qiu, Junlong Tong, Yao Zhang et al. |
|---|---|
| Primary category | cs.CL |
| Published | 20 June 2026 |
| Last updated at source | 20 June 2026 |
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