SciTS: Scientific Time Series Understanding and Generation with LLMs

SciTS: Scientific Time Series Understanding and Generation with LLMs This repository contains the official dataset for SciTS: Scientific Time Series Understanding and Generation with LLMs (ICLR 2026). SciTS is a large-scale benchmark designed to evaluate the capabilities of large language models on complex scientific time series data. It spans 12 scientific disciplines, 43 distinct tasks, and includes 54,023 instances. Dataset Structure The benchmark is organized… See the full description on the dataset page:

Source: Hugging Face Hub (OpenTSLab/SciTS). Metadata imported from the dataset’s Hub tags.