---
title: MMGR
canonical_url: "https://www.modelscope.cn/datasets/ZefanCai/MMGR"
md_url: "https://www.modelscope.cn/datasets/ZefanCai/MMGR.md"
repository: ZefanCai/MMGR
last_updated: 2026-09-24
license: other
storage_size: "20 GB"
downloads: 312
stars: 0
---

# MMGR

> MMGR - ZefanCai 在 ModelScope 开源的数据集。This repository is the public release mirror for the MMGR benchmark assets that are currently organized under code/ and data/.

ZefanCai/MMGR 是 ModelScope 魔搭社区上的数据集，存储大小 20 GB，采用 other 许可。

- **Repository**: ZefanCai/MMGR
- **License**: other
- **Storage size**: 20 GB
- **Downloads**: 312
- **Stars**: 0
- **Last updated**: 2026-09-24

Source: https://www.modelscope.cn/datasets/ZefanCai/MMGR

---

# MMGR-Open

This repository is the public release mirror for the MMGR benchmark assets that are currently organized under `code/` and `data/`.

## Layout

```text
code/   Evaluation prompts and scripts.
data/   Input images, generation prompts, ground-truth solutions where applicable.
```

The machine-readable release index is `dataset_manifest.json`.

## Dataset Manifest

`dataset_manifest.json` describes:

- task names and directory locations;
- sample counts for prompts, images, and solutions;
- how images, prompts, solutions, and task-level metadata are paired;
- which missing fields are intentional and which still require source mapping.

Use the manifest as the authoritative starting point for consuming this release.

## Pairing Rules

### Abstract Reasoning

ARC, Maze, and Sudoku provide one input image per ground-truth solution image. Their image and solution files are paired by matching task-specific filenames or relative directory structure.

Math uses rendered problem images plus aggregated JSON files under `data/solution/abstract_reasoning/math/`. The JSON files contain the corresponding problem statements and solutions.

### Embodied Navigation

Embodied-navigation prompt templates live in `data/prompt/embodied_nav/<task>/`.

For color-goal samples, the visible target is encoded in the input image and the matching floor/quality/turn subset directory.

For object-goal samples, prompts contain `{LOCATION_DESCRIPTION}`. Resolve that placeholder with:

```text
data/prompt/embodied_nav/location_descriptions_manifest.jsonl
```

Each JSONL record maps one public object-goal input image to its `location_description`, prompt template paths, subset directory, and source file. The original source text files are not required for normal use; if retained later, they should be treated only as optional human-readable copies under `data/prompt/embodied_nav/location_descriptions/<task>/<subset_dir>/<sample_id>.txt`.

The location-description manifest follows the canonical benchmark split: 60 object-goal records per embodied-navigation task, 240 records total. It does not include fallback records from another quality or subset.

Embodied-navigation images also follow the canonical benchmark split: each of the four tasks has 60 color-goal input images and 60 object-goal input images, for 480 navigation images total.

Navigation ground-truth solution files are not included in this release mirror yet. Their source mapping is still pending.

### Physical Commonsense

Physical commonsense is a prompt-driven video-generation/evaluation task. It does not require input images or solution images in this release layout. The prompt JSON files under `data/prompt/physical_commonsense/` define the generation prompts; the VLM evaluation prompt is under `code/physical_commonsense/vlm_based_evaluation/`.

`sports_prompts.json` already contains `prompt`, `physics_focus`, and `expected_motion`. `physical_concept_prompts.json` still needs an explicit mapping for the VLM placeholders `prompt_text`, `physics_info`, and `expected_motion`.

## Known Missing Or Pending Items

- `data/metadata/` is not present. The root `dataset_manifest.json` currently serves as the release-level manifest, but task-level metadata may still need to be added.
- Embodied-navigation solutions are not present and still require an approved mapping from source ground-truth files.
- Physical commonsense images and solutions are intentionally absent for the current prompt-only video task design.
- Two duplicate Google Drive math JSON files were observed during local sync; the local mirror collapsed them to unique files.