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+ # MTBench: A Multimodal Time Series Benchmark
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+ **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.
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+ 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.
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+ ## 📦 MTBench Datasets
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+ ### 🔹 Finance Domain
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+ - [`MTBench_finance_news`](https://huggingface.co/datasets/afeng/MTBench_finance_news)
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+ 20,000 articles with URL, timestamp, context, and labels
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+
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+ - [`MTBench_finance_stock`](https://huggingface.co/datasets/afeng/MTBench_finance_stock)
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+ Time series of 2,993 stocks (2013–2023)
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+ - [`MTBench_finance_aligned_pairs_short`](https://huggingface.co/datasets/afeng/MTBench_finance_aligned_pairs_short)
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+ 2,000 news–series pairs
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+ - Input: 7 days @ 5-min
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+ - Output: 1 day @ 5-min
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+ - [`MTBench_finance_aligned_pairs_short_multi`](https://huggingface.co/datasets/afeng/MTBench_finance_aligned_pairs_short_multi)
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+ 2,000 news–series pairs with multivariable
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+ - Input: 7 days @ 5-min
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+ - Output: 1 day @ 5-min
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+
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+ - [`MTBench_finance_aligned_pairs_long`](https://huggingface.co/datasets/afeng/MTBench_finance_aligned_pairs_long)
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+ 2,000 news–series pairs
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+ - Input: 30 days @ 1-hour
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+ - Output: 7 days @ 1-hour
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+ - [`MTBench_finance_aligned_pairs_long_multi`](https://huggingface.co/datasets/afeng/MTBench_finance_aligned_pairs_long_multi)
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+ 2,000+ news–series pairs with multi-variable
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+ - Input: 30 days @ 1-hour
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+ - Output: 7 days @ 1-hour
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+
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+ - [`MTBench_finance_QA_short`](https://huggingface.co/datasets/afeng/MTBench_finance_QA_short)
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+ 490 multiple-choice QA pairs
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+ - Input: 7 days @ 5-min
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+ - Output: 1 day @ 5-min
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+
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+ - [`MTBench_finance_QA_long`](https://huggingface.co/datasets/afeng/MTBench_finance_QA_long)
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+ 490 multiple-choice QA pairs
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+ - Input: 30 days @ 1-hour
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+ - Output: 7 days @ 1-hour
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+
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+ ### 🔹 Weather Domain
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+ - [`MTBench_weather_news`](https://huggingface.co/datasets/afeng/MTBench_weather_news)
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+ Regional weather event descriptions
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+ - [`MTBench_weather_temperature`](https://huggingface.co/datasets/afeng/MTBench_weather_temperature)
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+ Meteorological time series from 50 U.S. stations
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+ - [`MTBench_weather_aligned_pairs_short`](https://huggingface.co/datasets/afeng/MTBench_weather_aligned_pairs_short)
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+ Short-range aligned weather text–series pairs
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+
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+ - [`MTBench_weather_aligned_pairs_long`](https://huggingface.co/datasets/afeng/MTBench_weather_aligned_pairs_long)
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+ Long-range aligned weather text–series pairs
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+
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+ - [`MTBench_weather_aligned_pairs_short_multi`](https://huggingface.co/datasets/afeng/MTBench_weather_aligned_pairs_short_multi)
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+ Short-range aligned weather text–series pairs with multi-variables
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+
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+ - [`MTBench_weather_aligned_pairs_long_multi`](https://huggingface.co/datasets/afeng/MTBench_weather_aligned_pairs_long_multi)
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+ Long-range aligned weather text–series pairs with multi-variables
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+
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+ - [`MTBench_weather_QA_short`](https://huggingface.co/datasets/afeng/MTBench_weather_QA_short)
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+ Short-horizon QA with aligned weather data
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+ - [`MTBench_weather_QA_long`](https://huggingface.co/datasets/afeng/MTBench_weather_QA_long)
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+ Long-horizon QA for temporal and contextual reasoning
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+ ## 🧠 Supported Tasks
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+ MTBench supports a wide range of multimodal and temporal reasoning tasks, including:
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+ - 📈 **News-aware time series forecasting**
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+ - 📊 **Event-driven trend analysis**
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+ - ❓ **Multimodal question answering (QA)**
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+ - 🔄 **Text-to-series correlation analysis**
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+ - 🧩 **Causal inference in financial and meteorological systems**
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+ ## 📄 Citation
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+ If you use MTBench in your work, please cite:
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+ ```bibtex
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+ @article{chen2025mtbench,
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+ title={MTBench: A Multimodal Time Series Benchmark for Temporal Reasoning and Question Answering},
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+ 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},
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+ journal={arXiv preprint arXiv:2503.16858},
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+ year={2025}
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+ }