| # MTBench: A Multimodal Time Series Benchmark | |
| **MTBench** ([Huggingface](https://huggingface.co/collections/afeng/mtbench-682577471b93095c0613bbaa), [Github](https://github.com/Graph-and-Geometric-Learning/MTBench), [Arxiv](https://arxiv.org/pdf/2503.16858)) is a suite of multimodal datasets for evaluating large language models (LLMs) in temporal and cross-modal reasoning tasks across **finance** and **weather** domains. | |
| Each benchmark instance aligns high-resolution time series (e.g., stock prices, weather data) with textual context (e.g., news articles, QA prompts), enabling research into temporally grounded and multimodal understanding. | |
| ## 📦 MTBench Datasets | |
| ### 🔹 Finance Domain | |
| - [`MTBench_finance_news`](https://huggingface.co/datasets/afeng/MTBench_finance_news) | |
| 20,000 articles with URL, timestamp, context, and labels | |
| - [`MTBench_finance_stock`](https://huggingface.co/datasets/afeng/MTBench_finance_stock) | |
| Time series of 2,993 stocks (2013–2023) | |
| - [`MTBench_finance_aligned_pairs_short`](https://huggingface.co/datasets/afeng/MTBench_finance_aligned_pairs_short) | |
| 2,000 news–series pairs | |
| - Input: 7 days @ 5-min | |
| - Output: 1 day @ 5-min | |
| - [`MTBench_finance_aligned_pairs_long`](https://huggingface.co/datasets/afeng/MTBench_finance_aligned_pairs_long) | |
| 2,000 news–series pairs | |
| - Input: 30 days @ 1-hour | |
| - Output: 7 days @ 1-hour | |
| - [`MTBench_finance_QA_short`](https://huggingface.co/datasets/afeng/MTBench_finance_QA_short) | |
| 490 multiple-choice QA pairs | |
| - Input: 7 days @ 5-min | |
| - Output: 1 day @ 5-min | |
| - [`MTBench_finance_QA_long`](https://huggingface.co/datasets/afeng/MTBench_finance_QA_long) | |
| 490 multiple-choice QA pairs | |
| - Input: 30 days @ 1-hour | |
| - Output: 7 days @ 1-hour | |
| ### 🔹 Weather Domain | |
| - [`MTBench_weather_news`](https://huggingface.co/datasets/afeng/MTBench_weather_news) | |
| Regional weather event descriptions | |
| - [`MTBench_weather_temperature`](https://huggingface.co/datasets/afeng/MTBench_weather_temperature) | |
| Meteorological time series from 50 U.S. stations | |
| - [`MTBench_weather_aligned_pairs_short`](https://huggingface.co/datasets/afeng/MTBench_weather_aligned_pairs_short) | |
| Short-range aligned weather text–series pairs | |
| - [`MTBench_weather_aligned_pairs_long`](https://huggingface.co/datasets/afeng/MTBench_weather_aligned_pairs_long) | |
| Long-range aligned weather text–series pairs | |
| - [`MTBench_weather_QA_short`](https://huggingface.co/datasets/afeng/MTBench_weather_QA_short) | |
| Short-horizon QA with aligned weather data | |
| - [`MTBench_weather_QA_long`](https://huggingface.co/datasets/afeng/MTBench_weather_QA_long) | |
| Long-horizon QA for temporal and contextual reasoning | |
| ## 🧠 Supported Tasks | |
| MTBench supports a wide range of multimodal and temporal reasoning tasks, including: | |
| - 📈 **News-aware time series forecasting** | |
| - 📊 **Event-driven trend analysis** | |
| - ❓ **Multimodal question answering (QA)** | |
| - 🔄 **Text-to-series correlation analysis** | |
| - 🧩 **Causal inference in financial and meteorological systems** | |
| ## 📄 Citation | |
| If you use MTBench in your work, please cite: | |
| ```bibtex | |
| @article{chen2025mtbench, | |
| title={MTBench: A Multimodal Time Series Benchmark for Temporal Reasoning and Question Answering}, | |
| author={Chen, Jialin and Feng, Aosong and Zhao, Ziyu and Garza, Juan and Nurbek, Gaukhar and Qin, Cheng and Maatouk, Ali and Tassiulas, Leandros and Gao, Yifeng and Ying, Rex}, | |
| journal={arXiv preprint arXiv:2503.16858}, | |
| year={2025} | |
| } | |