umd-zhou-lab/TSRBench
TSRBench ๐ Paper | ๐ Project Page | ๐ป GitHub TSRBench is a large-scale, comprehensive benchmark designed to stress-test the time series understanding and reasoning capabilities of generalist models (LLMs, VLMs, and TSLLMs). Time series data pervades real-world environments and underpins decision-making in high-stakes domains like finance, healthcare, and industrial systems. However, existing benchmarks often treat time series as isolated numerical sequences, stripping awayโฆ See the full description on the dataset page: https://huggingface.co/datasets/umd-zhou-lab/TSRBench.
| Author / organization | umd-zhou-lab |
|---|---|
| Downloads | 291 (as reported by Hugging Face) |
| Likes | 3 |
| Created | 25 January 2026 |
| Last updated at source | 27 January 2026 |
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291 now (+3 since 2026-10-16). Counts as reported by the source, snapshotted daily by Silytics.
Recent changes
- 17 Oct 2026 Description: TSRBench ๐ Paper | ๐ Project Page | ๐ป GitHub TSRBench is a large-scale, comprehensive benchmark designed to stress-test the time series understanding and reasoning capabilities of generalist models (LLMs, VLMs, and TSLLMs). Time series d โ TSRBench ๐ Paper | ๐ Project Page | ๐ป GitHub TSRBench is a large-scale, comprehensive benchmark designed to stress-test the time series understanding and reasoning capabilities of generalist models (LLMs, VLMs, and TSLLMs). Time series d
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