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--- |
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license: cc-by-nc-sa-4.0 |
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configs: |
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- config_name: Math |
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data_files: |
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- split: test |
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path: Math/test-* |
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- split: val |
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path: Math/val-* |
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- config_name: Physics |
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data_files: |
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path: Physics/test-* |
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- split: val |
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path: Physics/val-* |
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- config_name: Chemistry |
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data_files: |
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path: Chemistry/test-* |
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path: Chemistry/val-* |
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- config_name: Biology |
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data_files: |
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path: Biology/test-* |
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path: Biology/val-* |
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- config_name: Geography |
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data_files: |
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- split: test |
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path: Geography/test-* |
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path: Geography/val-* |
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data_files: |
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- split: test |
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path: Astronomy/test-* |
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path: Astronomy/val-* |
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- config_name: CS |
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data_files: |
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- split: test |
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path: CS/test-* |
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- split: val |
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path: CS/val-* |
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task_categories: |
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- question-answering |
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language: |
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- en |
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- zh |
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pretty_name: OlympicArena |
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size_categories: |
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- 10K<n<100K |
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tags: |
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- croissant |
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--- |
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# OlympicArena: Benchmarking Multi-discipline Cognitive Reasoning for Superintelligent AI |
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**OlympicArena** is a comprehensive, highly-challenging, and rigorously curated benchmark featuring a detailed, fine-grained evaluation mechanism designed to assess advanced AI capabilities across a broad spectrum of Olympic-level challenges. |
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This benchmark encompasses seven disciplines: Mathematics, Physics, Chemistry, Biology, Geography, Astronomy, and Computer Science. Each discipline is divided into two splits: validation (val) and test. The validation split includes publicly available answers for small-scale testing and evaluation, while the test split does not disclose the answers, ensuring an unbiased assessment of AI performance. |
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# An Example to load the data |
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```python |
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from datasets import load_dataset |
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dataset=load_dataset("GAIR/OlympicArena", "Math", split="val") |
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print(dataset[0]) |
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``` |
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More details on loading and using the data are at our [github page](https://github.com/GAIR-NLP/OlympicArena). |
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