---
pretty_name: SciCode-Verified
license: apache-2.0
language:
- en
annotations_creators:
- expert-generated
source_datasets:
- extended
task_categories:
- text-generation
size_categories:
- n<1K
tags:
- code
- science
- benchmark
- code-generation
- scientific-coding
- llm-evaluation
configs:
- config_name: default
  data_files:
  - split: test
    path: data/problems_test.jsonl
---

# SciCode-Verified

SciCode-Verified is the corrected, human-verified release of the
[SciCode](https://github.com/scicode-bench/SciCode) scientific-code-generation benchmark.
A problem-by-problem audit identified 263 defects in the 65-problem SciCode test split and
corrected every confirmable defect. The released evaluation set contains 64 main problems and
287 scored subproblems; one original problem is excluded because its specification does not
determine a unique, verifiable answer.

- **Paper:** [SciCode-Verified: How Benchmark Defects Underestimated the Scientific-Coding Ability of Language Models](https://arxiv.org/abs/2608.04975)
- **Code, evaluation harness, and audit trail:** [github.com/flyingwagner/scicode-verified](https://github.com/flyingwagner/scicode-verified)
- **Original benchmark:** [SciCode](https://arxiv.org/abs/2407.13168)

## Files

| File | Purpose |
|---|---|
| `data/problems_test.jsonl` | Corrected prompts and problem specifications, one main problem per line |
| `test_data_cleaned.h5` | Corrected frozen grading targets used by the evaluation harness |
| `manifest.json` | Release version, problem order, and MD5 checksums |
| `LICENSE` | Apache License 2.0 inherited from the upstream benchmark |

Release `v2` checksums:

```text
5c604d8dbf52642bd94e13b92c8f52eb  data/problems_test.jsonl
2b41a7df40ddc23ce651ec05b8ecb6f8  test_data_cleaned.h5
```

## Load the problem specifications

```python
from datasets import load_dataset

dataset = load_dataset("shhu2001/SciCode-Verified", split="test")
print(dataset[0])
```

## Download the grading targets

```python
from huggingface_hub import hf_hub_download

h5_path = hf_hub_download(
    repo_id="shhu2001/SciCode-Verified",
    repo_type="dataset",
    filename="test_data_cleaned.h5",
)
```

The full generation, grading, multi-environment evaluation, and integrity-check workflow is
documented in the [GitHub repository](https://github.com/flyingwagner/scicode-verified). Model
outputs and evaluation logs are intentionally not included in this dataset repository.

## License and attribution

SciCode-Verified is derived from SciCode and redistributed under the Apache License 2.0. Please
cite both the original SciCode benchmark and SciCode-Verified.

```bibtex
@article{hu2026scicodeverified,
  title         = {{SciCode-Verified}: How Benchmark Defects Underestimated the Scientific-Coding Ability of Language Models},
  author        = {Hu, Sihan and Huang, Lyuhan and Deng, Youjin and Chen, Kun},
  year          = {2026},
  eprint        = {2608.04975},
  archivePrefix = {arXiv},
  primaryClass  = {cs.SE},
  url           = {https://arxiv.org/abs/2608.04975}
}

@article{tian2024scicode,
  title         = {{SciCode}: A Research Coding Benchmark Curated by Scientists},
  author        = {Tian, Minyang and Gao, Luyu and Zhang, Shizhuo Dylan and Chen, Xinan and others},
  year          = {2024},
  eprint        = {2407.13168},
  archivePrefix = {arXiv},
  primaryClass  = {cs.AI},
  url           = {https://arxiv.org/abs/2407.13168}
}
```