task_categories:text-generation task_categories:question-answering language:en license:cc-by-nc-sa-4.0 size_categories:100K<n<1M arxiv:2501.15587 region:us chemistry biology medical
---
license: cc-by-nc-sa-4.0
task_categories:
- text-generation
- question-answering
language:
- en
size_categories:
- 100K<n<1M
tags:
- chemistry
- biology
- medical
---
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# Dataset Card for SCP-116K
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## Dataset Description

### Paper

[SCP-116K: A High-Quality Problem-Solution Dataset and a Generalized Pipeline for Automated Extraction in the Higher Education Science Domain
](https://arxiv.org/abs/2501.15587)
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### Dataset Summary
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SCP-116K is a large-scale dataset containing 116,756 high-quality scientific problem-solution pairs, automatically extracted from web crawled documents. The dataset covers multiple scientific disciplines including physics, chemistry, and biology, targeting undergraduate to doctoral-level content. Each problem is accompanied by its matched solution, as well as solutions generated by advanced language models (o1-mini and QwQ-32B-preview) along with validation flags.

Github: https://github.com/AQA6666/SCP-116K-open/tree/main
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### Supported Tasks
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The dataset supports several tasks:
- Scientific Question Answering
- Scientific Reasoning
- Model Evaluation
- Knowledge Distillation
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### Languages
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The dataset is in English.
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### Dataset Structure
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The dataset contains the following columns:
- `domain`: The scientific domain of the problem (e.g., physics, chemistry, biology)
- `problem`: The original problem text
- `matched_solution`: The matched solution extracted from the source material
- `o1_solution`: Solution generated by the o1-mini model
- `is_o1_solution_same_with_matched_solution`: Boolean flag indicating whether o1's solution matches the ground truth
- `qwq_solution`: Solution generated by the QwQ-32B-preview model
- `is_qwq_solution_same_with_matched_solution`: Boolean flag indicating whether QwQ's solution matches the ground truth
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### Data Fields
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- `domain`: string
- `problem`: string
- `matched_solution`: string
- `o1_solution`: string
- `is_o1_solution_same_with_matched_solution`: bool
- `qwq_solution`: string
- `is_qwq_solution_same_with_matched_solution`: bool
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### Data Splits
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The dataset is provided as a single split containing all 116,756 examples.
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## Dataset Creation
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### Source Data
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The dataset was created by processing over 6.69 million academic documents, filtering for high-quality university-level content, and extracting problem-solution pairs using a sophisticated automated pipeline. The extraction process includes document retrieval, unified preprocessing, content segmentation, structured extraction, quality filtering, and problem-solution matching.
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### Annotations
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The dataset includes solutions generated by two state-of-the-art language models:
- o1-mini
- QwQ-32B-preview
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Each generated solution is validated against the ground truth solution extracted from the source material.
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## Considerations for Using the Data
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### Social Impact of Dataset
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This dataset aims to advance scientific reasoning capabilities in AI systems and provide high-quality training data for developing more capable models in STEM disciplines. It can help democratize access to advanced scientific problem-solving capabilities and support education in scientific fields.
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### Discussion of Biases
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While efforts have been made to ensure high quality and diversity in the dataset, users should be aware that:
- The dataset may reflect biases present in web crawled documents
- Coverage across different scientific domains may not be perfectly balanced
- The difficulty level of problems varies across the dataset
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### Other Known Limitations
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- Solutions may occasionally reference figures or equations not included in the text
- Some problems may require specialized domain knowledge for full understanding
- The dataset focuses primarily on theoretical problems rather than experimental ones
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## Additional Information
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### Dataset Curators
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The dataset was created as part of research work on improving scientific reasoning capabilities in language models.
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### Licensing Information
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This dataset is released under the cc-by-nc-sa-4.0 License.
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### Citation Information
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If you use this dataset in your research, please cite:
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```bibtex
@misc{lu2025scp116khighqualityproblemsolutiondataset,
      title={SCP-116K: A High-Quality Problem-Solution Dataset and a Generalized Pipeline for Automated Extraction in the Higher Education Science Domain}, 
      author={Dakuan Lu and Xiaoyu Tan and Rui Xu and Tianchu Yao and Chao Qu and Wei Chu and Yinghui Xu and Yuan Qi},
      year={2025},
      eprint={2501.15587},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2501.15587}, 
}
```
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### Contributions
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Thanks to all contributors who helped create and maintain this dataset. Contributions to improve the dataset are welcome! Please check the GitHub repository for contribution guidelines.