---
annotations_creators:
- machine-generated
language:
- en
license:
- other
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
task_categories:
- image-to-text
- visual-question-answering
task_ids:
- visual-question-answering
---

# RobustRDP-ProcessedValData

Processed validation/evaluation data for the paper: *RobustRDP: Advancing Reaction Diagram Parsing via Synthetic-to-Real Data Scaling and Robustness-Oriented Training*.

## Dataset Structure

```
RobustRDP_test/
├── dev_downsampled_rxn.json         # Validation entries
└── images_eval_resized.zip          # Zipped evaluation images (500 images)

RxnScribe_test/
├── dev_downsampled_rxn.json         # Validation entries
└── images_eval_resized.zip          # Zipped evaluation images (1,379 images)
```

## Data Details

| Split | Entries | Images | Description |
|-------|---------|--------|-------------|
| **RobustRDP_test** | 500 | 500 | RobustRDP evaluation set covering multiple reaction diagram parsing variants |
| **RxnScribe_test** | 138 | 1,379 | RxnScribe evaluation set for reaction diagram parsing benchmark |

## Data Format

Each entry follows the conversational format:

```json
{
    "messages": [
        {"content": "<image>\n...", "role": "user"},
        {"content": "<rxn><rct>...<mol><cnd>...<txt><prd>...<mol>", "role": "assistant"}
    ],
    "images": ["path/to/image.png"]
}
```

Annotations use special tokens:
- `<rxn>`: Start of a reaction
- `<rct>`: Reactants section
- `<cnd>`: Conditions section
- `<prd>`: Products section
- `<mol>`: Molecule entity
- `<txt>`: Text entity

## Data Generation

Evaluation data built from [RxnLabelData](https://huggingface.co/datasets/Jingcz/RxnLabelData), downsampled and processed for model evaluation on reaction diagram parsing tasks.

## Related Resources

- **Model**: [RobustRDP](https://huggingface.co/Jingcz/RobustRDP)
- **Raw Data**: [RobustRDP-RawValData](https://huggingface.co/datasets/Jingcz/RobustRDP-RawValData)
- **Code**: [RobustRDP GitHub](https://github.com/jaydetang/RobustRDP)
- **Annotation Platform**: [RxnLabel](https://github.com/jaydetang/RxnLabel)