| --- |
| license: cc-by-4.0 |
| language: |
| - zh |
| pretty_name: MoveBench Rubrics and Answer Keys |
| size_categories: |
| - n<1K |
| task_categories: |
| - question-answering |
| tags: |
| - sports |
| - health |
| - rubric |
| - evaluation |
| - arxiv:2610.26185 |
| configs: |
| - config_name: default |
| data_files: |
| - split: test |
| path: annotations.jsonl |
| --- |
| <!-- MoveBench brand header --> |
| <p align="center" style="margin:0;padding:0;line-height:1.2;"> |
| <img src="assets/movebench-multicolor-badge.png" alt="MoveBench" width="420" style="display:inline-block;margin:0;vertical-align:bottom;" /><br /> |
| <a href="https://github.com/Keep-Tech/MoveBench"><img src="https://img.shields.io/badge/GitHub-MoveBench-181717?style=flat-square&logo=github&logoColor=white" alt="GitHub dataset repository" /></a> |
| <a href="https://arxiv.org/abs/2610.26185"><img src="https://img.shields.io/badge/Paper-arXiv%3A2610.26185-B31B1B?style=flat-square&logo=arxiv&logoColor=white" alt="MoveBench paper on arXiv" /></a> |
| <a href="https://keepace.ai/"><img src="https://img.shields.io/badge/Website-Keepace.ai-00A884?style=flat-square" alt="Keepace.ai official website" /></a> |
| </p> |
| <!-- /MoveBench brand header --> |
|
|
|
|
| # MoveBench Rubrics and Answer Keys |
|
|
| **An annotation-only companion to [KeepaceAI/MoveBench](https://huggingface.co/datasets/KeepaceAI/MoveBench).** |
|
|
| This separate dataset contains annotations for the existing **80 public questions**: **30 multiple-choice answer keys** and **464 rubric criteria across 50 open-ended questions**. Join records to the original questions using `problem_id`. This repository does not repeat question text or choices and does not include open-ended reference answers. The original questions-only dataset remains unchanged. |
|
|
| [Original questions](https://huggingface.co/datasets/KeepaceAI/MoveBench) · [Paper](https://arxiv.org/abs/2610.26185) · [GitHub](https://github.com/Keep-Tech/MoveBench) |
|
|
| ## Usage |
|
|
| ```python |
| from datasets import load_dataset |
| |
| questions = load_dataset("KeepaceAI/MoveBench", split="test") |
| annotations = load_dataset("KeepaceAI/MoveBench-Rubrics", split="test") |
| annotations_by_id = {row["problem_id"]: row for row in annotations} |
| for question in questions: |
| annotation = annotations_by_id[question["problem_id"]] |
| # Generate model answers from question inputs only. |
| # Use annotation["rubric"] or annotation["answer_key"] for evaluation. |
| ``` |
|
|
| Do not pass answers or rubrics to the student model when generating evaluation responses. |
|
|
| ## Expert contribution and rubric development |
|
|
| **The released rubrics have been reviewed and calibrated by sports-domain experts to clarify item-specific assessment requirements.** |
|
|
| According to the project team's production records, **26 experts** contributed to the full 809-question benchmark over **20 days**, with **2,912 expert-hours** across question drafting, answer writing, review, re-review and inclusion in the benchmark. The team comprises **17 experts and contributors affiliated with Keep, Beijing, China**, and **9 affiliated with Capital University of Physical Education and Sports, Beijing, China**. These figures refer to the entire project, not solely rubric writing or the 80-question release. They do not imply that all 26 experts reviewed every item. |
|
|
| The team reports 2,059,649 characters of project material, approximately 2,546 characters and 3.6 expert-hours per question. These are project-reported production statistics, not independently audited measurements. |
|
|
| The published methodology combines scenario-specific question and rubric drafting, automated quality checks, and expert review. Criteria articulate assessable requirements such as goal alignment, exercise selection, clarity, and safety. Review considers question clarity, answer/rubric consistency, scientific validity and safety; items may be revised or excluded before inclusion. |
|
|
| ## Expert team and affiliations |
|
|
| The MoveBench team comprises **26 experts and contributors: 17 affiliated with Keep and 9 affiliated with Capital University of Physical Education and Sports** |
|
|
| ## Participation |
| If you'd like to evaluate your model's capabilities in sports and health-related scenarios using the full MoveBench benchmark of 809 questions, we invite you to participate in our evaluation program. Our team of sports science professionals will provide a comprehensive evaluation report, free of charge, offering insights into your model's performance. Interested? Contact us at benchmarkcontact@keep.com. |
|
|
| ## Scope, license and limitations |
|
|
| The full project contains 809 questions; this companion annotates only the existing 80-question public subset. Published answers and rubrics make this an exposed research/development resource, not an unseen held-out test. Disclose prior exposure and benchmark-specific optimization. The materials are not medical advice or evidence of deployment safety. |
|
|
| Questions and rubrics originate from the company repository's public release. Descriptions and scores are preserved; MCQ answer labels are normalized to lists. All content here is licensed under **CC BY 4.0**; credit MoveBench Team and cite [the paper](https://arxiv.org/abs/2610.26185). The paper itself has a separate license. |
|
|
| ## 中文说明 |
|
|
| 这是独立的答案与评分标准数据集，不重复发布题干。包含原公开 80 题的题号、30 道选择题答案、50 道开放题的 464 条 rubric。通过 `problem_id` 与原始题库关联；不含开放题参考答案。专家人数和工时为完整 809 题项目整体投入。 |
|
|
| **本数据集中的 rubric 已经过运动领域专家审核与校准**，针对每道开放题明确评分要求，覆盖任务完成质量、科学性、可执行性及安全边界等方面，支持研究者检查和理解评分依据。专家审核与校准不等同于临床验证或对模型部署安全性的认证。 |
|
|
| 原题干与选项请见 [MoveBench 题目集](https://huggingface.co/datasets/KeepaceAI/MoveBench)，使用 `problem_id` 对齐：选择题读取 `answer_key`，开放题读取 `rubric`。模型生成回答时只输入题目及选项，不应将答案或 rubric 一并提供给被测模型。 |
|
|
| 完整 809 题项目由 **26 位专家与贡献者**参与，其中 **17 位来自 Keep **，**9 位来自首都体育学院 **。项目历时 20 天，投入 2,912 专家工时。 |
|
|
