OpenTSLM: Time-Series Language Models for Reasoning over Multivariate Medical Text- and Time-Series Data

Understand

LLMs have emerged as powerful tools for interpreting multimodal data.

• In medicine, they hold particular promise for synthesizing large volumes of clinical information into actionable insights and digital health applications.
• Yet, a major limitation remains their inability to handle time series.
• To overcome this gap, we present OpenTSLM, a family of Time Series Language Models (TSLMs) created by integrating time series as a native modality to pretrained LLMs, enabling reasoning over multiple time series of any length.