| --- |
| license: other |
| language: |
| - en |
| - zh |
| task_categories: |
| - visual-question-answering |
| - question-answering |
| pretty_name: SciDocBench |
| size_categories: |
| - n<1K |
| configs: |
| - config_name: default |
| data_files: |
| - split: test |
| path: data/test-*.parquet |
| --- |
| |
| # SciDocBench |
|
|
| Official data release for [SciDocBench: A Workflow-Centered Benchmark and Data |
| Pipeline for Scientific Document Understanding](https://arxiv.org/abs/2609.05141). |
| Project and evaluation code: [InternLM/SciDocBench](https://github.com/InternLM/SciDocBench). |
|
|
| ## Dataset Summary |
|
|
| SciDocBench contains 496 evaluation instances derived from |
| 124 expert-authored scientific-document questions. |
| Each question is represented under four matched settings that cross English/Chinese |
| questions with all-images-first/interleaved document representations. |
|
|
| | Partition | Instances | |
| |---|---:| |
| | EN, all images first | 124 | |
| | EN, interleaved | 124 | |
| | ZH, all images first | 124 | |
| | ZH, interleaved | 124 | |
|
|
| The release references 7,052 images across instances and |
| contains 2,758 unique image files after SHA-256 deduplication. |
|
|
| ## Files |
|
|
| - `data/test-00000-of-00001.parquet`: Hugging Face test split. |
| - `SciDocBench.tsv`: portable VLMEvalKit-compatible source table. |
| - `scidocbench.tsv`: compatibility alias for the original repository path. |
| - `images/SciDocBench/`: content-addressed document images. |
| - `release_manifest.json`: counts and checksums. |
| - `manifests/images.jsonl`: per-image hashes and reference counts. |
|
|
| In the Parquet file, `image_path` is a list of paths relative to the VLMEvalKit image |
| root, while `images` contains repository-relative paths. Interleaved `segments` retain |
| their ordering and refer to the rewritten `image_path` values. |
|
|
| ## Usage |
|
|
| Load the table with Hugging Face Datasets: |
|
|
| ```python |
| from datasets import load_dataset |
| |
| dataset = load_dataset("HenryExcellent/SciDocBench", split="test") |
| ``` |
|
|
| For a local VLMEvalKit checkout, download the repository and place the TSV and image |
| tree under `LMUData`: |
|
|
| ```bash |
| hf download HenryExcellent/SciDocBench --repo-type dataset --local-dir SciDocBench |
| |
| cp SciDocBench/SciDocBench.tsv "$LMUData/SciDocBench.tsv" |
| mkdir -p "$LMUData/images/SciDocBench" |
| cp -a SciDocBench/images/SciDocBench/. "$LMUData/images/SciDocBench/" |
| ``` |
|
|
| ## Evaluation |
|
|
| Use the SciDocBench integration in |
| [VLMEvalKit](https://github.com/open-compass/VLMEvalKit) for standardized inference |
| and evaluation. |
|
|
| ## License and Use |
|
|
| Benchmark annotations and scripts are released for research use under the terms stated |
| by the SciDocBench project. Paper pages and figures originate from heterogeneous |
| scientific sources and may retain source-specific copyright or license terms. Users |
| are responsible for checking the applicable terms before redistribution or commercial |
| use. No blanket license is asserted over third-party document imagery. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @article{wu2026scidocbench, |
| title = {SciDocBench: A Workflow-Centered Benchmark and Data Pipeline for Scientific Document Understanding}, |
| author = {Wu, Shenxi and Liu, Yuhong and Zhang, Haosong and Zou, Tongjin and Zhang, Yanxun and Chen, Gaochang and Liang, Dun and Wang, Jiaqi and Wang, Zhecan James and Zang, Yuhang and Lin, Dahua}, |
| journal = {arXiv preprint arXiv:2609.05141}, |
| year = {2026} |
| } |
| ``` |
|
|
