README.md

---
license: cc-by-nc-sa-4.0
task_categories:
- text-generation
- question-answering
language:
- en
size_categories:
- 100K<n<1M
tags:
- chemistry
- biology
- medical
- mathematics
---

# Dataset Card for SCP-378K

## 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)

### Dataset Summary

SCP-378K is a large-scale scientific problem-solution dataset containing **377,705 examples**. It is an improved version of SCP-116K with substantially enhanced solution coverage: **every problem is paired with a matched solution extracted from the source material**.

The dataset covers multiple scientific disciplines, including physics, chemistry, biology, medicine, and mathematics, targeting undergraduate to doctoral-level scientific content. Compared with SCP-116K, SCP-378K focuses on providing complete problem-solution pairs with extracted standard answers. Due to resource constraints, this version does not include DeepSeek-R1-generated responses or reasoning traces.

GitHub: [https://github.com/AQA6666/SCP-116K-open/tree/main](https://github.com/AQA6666/SCP-116K-open/tree/main)

Previous version with R1-generated responses and reasoning traces: [EricLu/SCP-116K](https://huggingface.co/datasets/EricLu/SCP-116K)

### Supported Tasks

The dataset supports several tasks:
- Scientific Question Answering
- Scientific Reasoning
- Text Generation
- Model Evaluation
- Supervised Fine-Tuning
- Reward Model / Verifier Training

### Languages

The dataset is in English.

### Dataset Structure

The dataset contains the following columns:
- `id`: A unique identifier for each example.
- `problem`: The original scientific problem text.
- `matched_solution`: The solution matched to the problem and extracted from the source material.

### Data Fields

- `id`: string / integer  
- `problem`: string  
- `matched_solution`: string  

### Data Splits

The dataset is provided as a single split containing all **377,705** examples.

---

## Relationship to SCP-116K

SCP-378K is a newer and improved version of SCP-116K. The main improvement is complete solution coverage: while SCP-116K contains many problems without extracted source solutions, every problem in SCP-378K is paired with a matched solution extracted from the source material.

However, SCP-378K does not include DeepSeek-R1-generated responses or reasoning traces. Users interested in R1-generated solutions and reasoning data may refer to the previous dataset: [EricLu/SCP-116K](https://huggingface.co/datasets/EricLu/SCP-116K).

| Dataset | # Examples | Matched / Extracted Solutions | R1 Responses | R1 Reasoning Traces |
|---|---:|---:|---:|---:|
| [SCP-116K](https://huggingface.co/datasets/EricLu/SCP-116K) | 274,166 | ~40K | Yes | Yes |
| **SCP-378K** | 377,705 | 377,705 | No | No |

---

## Dataset Creation

### Source Data

The dataset was created by processing large-scale web-crawled academic and educational documents, filtering for high-quality university-level scientific content, and extracting problem-solution pairs using an automated pipeline. The extraction process includes document retrieval, unified preprocessing, content segmentation, structured extraction, quality filtering, and problem-solution matching.

SCP-378K improves upon the previous version by addressing the solution extraction deficiency in SCP-116K, resulting in complete matched-solution coverage for all examples.

### Annotations

Each example contains a scientific problem and its corresponding matched solution extracted from the source material. Unlike SCP-116K, this dataset does not include model-generated responses or reasoning traces.

---

## Considerations for Using the Data

### Social Impact of Dataset

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.

### Discussion of Biases

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.
- Extracted solutions may inherit formatting issues or ambiguities from the original source documents.

### Other Known Limitations

- Solutions may occasionally reference figures, tables, 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.
- Matched solutions are automatically extracted and matched, so users should expect occasional noise or mismatches.

---

## Additional Information

### Dataset Curators

The dataset was created as part of research work on improving scientific reasoning capabilities in language models.

### Licensing Information

This dataset is released under the **cc-by-nc-sa-4.0 License**.

### Citation Information

If you use this dataset in your research, please cite:

```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}, 
}
```