Language Models Still Struggle to Zero-shot Reason about Time Series

arXiv:2404.11757v1 Announce Type: new
Abstract: Time series are critical for decision-making in fields like finance and healthcare. Their importance has driven a recent influx of works passing time series into language models, leading to non-trivial forecasting on some datasets. But it remains unknown whether non-trivial forecasting implies that language models can reason about time series. To address this gap, we generate a first-of-its-kind evaluation framework for time series reasoning, including formal tasks and a corresponding dataset of multi-scale time series …

abstract arxiv cs.cl datasets decision fields finance forecasting healthcare importance language language models making reason series struggle time series type zero-shot