| --- |
| license: cc-by-nc-sa-4.0 |
| task_categories: |
| - visual-question-answering |
| - multiple-choice |
| language: |
| - en |
| pretty_name: HumaniBench-MCQ |
| size_categories: |
| - 1K<n<10K |
| configs: |
| - config_name: default |
| data_files: |
| - split: test |
| path: data/test-* |
| --- |
| # HumaniBench-MCQ: Task 3 (Multiple-Choice VQA) in MMMU Format |
|
|
| <p align="center"> |
| <img src="https://github.com/user-attachments/assets/ebed8e26-5bdf-48c1-ae41-0775b8c33c0a" alt="HumaniBench Logo" height="120"/> |
| </p> |
|
|
| This dataset is a **format conversion** of Task 3 (`task3_Multiple_Choice_VQA`) from [HumaniBench](https://huggingface.co/datasets/vector-institute/HumaniBench), restructured to match the [MMMU](https://huggingface.co/datasets/MMMU/MMMU) schema so it can be used directly with MMMU-style evaluation pipelines. |
|
|
| **No questions, images, or answers were added, removed, or changed.** Only the column layout and answer format differ from the original. |
|
|
| <p align="center"> |
| <a href="https://vectorinstitute.github.io/HumaniBench/"><img src="https://img.shields.io/badge/🌐-Website-4285F4" alt="Website"></a> |
| <a href="https://arxiv.org/abs/2505.11454"><img src="https://img.shields.io/badge/arXiv-Paper-b31b1b?logo=arxiv&logoColor=white" alt="Paper"></a> |
| <a href="https://github.com/VectorInstitute/HumaniBench"><img src="https://img.shields.io/badge/GitHub-Code-181717?logo=github" alt="Code"></a> |
| <a href="https://huggingface.co/datasets/vector-institute/HumaniBench"><img src="https://img.shields.io/badge/🤗-Original%20Dataset-FFD21F" alt="Original Dataset"></a> |
| </p> |
|
|
| --- |
|
|
| ## How to Load |
|
|
| ```python |
| from datasets import load_dataset |
| |
| ds = load_dataset("vector-institute/HumaniBench-MCQ", split="test") |
| ``` |
|
|
| --- |
|
|
| ## Dataset Structure |
|
|
| 1,844 multiple-choice questions, one image each, in a single `test` split. |
|
|
| | Column | Type | Description | |
| |---|---|---| |
| | `id` | string | MMMU-style ID: `test_<Attribute>_<n>`, numbered within each attribute (e.g., `test_Gender_1`) | |
| | `question` | string | Question text, prefixed with the `<image 1>` placeholder | |
| | `options` | string | String-formatted list of answer choices, without letter prefixes (e.g., `['Male', 'Female', 'Non-binary', 'Gender-neutral']`) | |
| | `explanation` | string | Reasoning supporting the answer (optional; not required for evaluation) | |
| | `image_1` | image | Embedded image data | |
| | `img_type` | string | Image type, always `['Photographs']` | |
| | `answer` | string | Single-letter answer (e.g., `B`) | |
| | `demographic` | string | HumaniBench attribute being tested (e.g., Gender, Age). Used as the categorical field for grouping results (takes the place of MMMU's `topic_difficulty`) | |
| | `question_type` | string | Always `multiple-choice` | |
| | `subfield` | string | Left empty | |
| | `original_id` | string | ID from the original HumaniBench Task 3, for traceability | |
|
|
| ### Example |
|
|
| ``` |
| id: test_Gender_2 |
| question: <image 1> What gender representation is depicted by the statue of Lady Justice? |
| options: ['Male', 'Female', 'Non-binary', 'Gender-neutral'] |
| answer: B |
| demographic: Gender |
| question_type: multiple-choice |
| original_id: c6caaf72e5 |
| ``` |
|
|
| --- |
|
|
| ### Differences from MMMU |
|
|
| - Only `image_1` is included, since every question uses a single image. MMMU's `image_2` to `image_7` columns are omitted. |
| - MMMU's `topic_difficulty` column is replaced by `demographic`, which holds the attribute being tested. |
| - `original_id` is an extra column not present in MMMU. |
|
|
| --- |
|
|
| ## Intended Use |
|
|
| - Evaluating multimodal models on human-centric multiple-choice VQA using MMMU-compatible evaluation code |
| - Comparing model accuracy across social attributes via `demographic` |
|
|
| For the full benchmark (7 tasks, 32,000+ image–question pairs), see the [original HumaniBench dataset](https://huggingface.co/datasets/vector-institute/HumaniBench). |
|
|
| --- |
|
|
| ## Related Resources |
|
|
| - [Original HumaniBench Dataset](https://huggingface.co/datasets/vector-institute/HumaniBench) |
| - [Project Website](https://vectorinstitute.github.io/HumaniBench/) |
| - [GitHub Repository](https://github.com/VectorInstitute/HumaniBench) |
| - [Paper (arXiv)](https://arxiv.org/abs/2505.11454) |
| - [MMMU Dataset](https://huggingface.co/datasets/MMMU/MMMU) (format reference) |
|
|
| --- |
|
|
| ## License |
|
|
| This dataset is licensed under the **CC BY-NC-SA 4.0 License**, the same as the original HumaniBench. |
|
|
| --- |
|
|
| ## 🙏 Acknowledgments |
|
|
| Resources used in preparing this research were provided, in part, by the Province of Ontario, the Government of Canada through CIFAR, and companies sponsoring the Vector Institute ([vectorinstitute.ai/#partners](http://www.vectorinstitute.ai/#partners)). |
|
|
| This research was funded by the European Union's Horizon Europe research and innovation programme under the AIXPERT project (Grant Agreement No. 101214389), which aims to develop an agentic, multi-layered, GenAI-powered framework for creating explainable, accountable, and transparent AI systems. |
|
|
| --- |
|
|
| ## 📚 Citation |
|
|
| If you use this dataset, please cite the original HumaniBench paper: |
|
|
| ```bibtex |
| @article{raza2026humanibench, |
| author = {Raza, Shaina and Narayanan, Aravind and Khazaie, Vahid Reza and Vayani, Ashmal and Radwan, Ahmed Y. and Chettiar, Mukund S. and Singh, Amandeep and Shah, Mubarak and Pandya, Deval}, |
| title = {HumaniBench: A Human-Centric Framework for Large Multimodal Models Evaluation}, |
| year = {2026}, |
| publisher = {Association for Computing Machinery}, |
| address = {New York, NY, USA}, |
| issn = {2157-6904}, |
| url = {https://doi.org/10.1145/3845999}, |
| doi = {10.1145/3845999}, |
| note = {Just Accepted}, |
| journal = {ACM Trans. Intell. Syst. Technol.}, |
| month = sep, |
| } |
| ``` |
