ZhiqiGao/TPBench
TP Bench – Theoretical Physics Benchmark for AI TPBench is a curated dataset and evaluation suite designed to measure the reasoning capabilities of AI models in theoretical physics. Our test problems span multiple difficulty levels—from undergraduate to frontier research—and cover topics such as cosmology, high-energy theory, general relativity, and more. By providing a unified framework for problem-solving and auto-verifiable answers, TPBench aims to drive progress in… See the full description on the dataset page: https://huggingface.co/datasets/ZhiqiGao/TPBench.
| Author / organization | ZhiqiGao |
|---|---|
| License (as declared) | mit |
| Downloads | 124 (as reported by Hugging Face) |
| Likes | 6 |
| Created | 11 March 2025 |
| Last updated at source | 19 May 2025 |
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124 now (-7 since 2026-10-16). Counts as reported by the source, snapshotted daily by Silytics.
Recent changes
- 16 Oct 2026 Description: TP Bench – Theoretical Physics Benchmark for AI TPBench is a curated dataset and evaluation suite designed to measure the reasoning capabilities of AI models in theoretical physics. Our test problems span multiple difficulty levels—from und → TP Bench – Theoretical Physics Benchmark for AI TPBench is a curated dataset and evaluation suite designed to measure the reasoning capabilities of AI models in theoretical physics. Our test problems span multiple difficulty levels—from und
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Silytics shows public metadata from Hugging Face and links to the original. Information may be incomplete or out of date. Last refreshed 17 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.