---
annotations_creators:
- machine-generated
language:
- en
license:
- other
multilinguality:
- monolingual
size_categories:
- 100K<n<1M
task_categories:
- image-to-text
- visual-question-answering
task_ids:
- visual-question-answering
---

# RobustRDP-ProcessedTrainData

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

## Dataset Structure

```
pretrain_data/
├── pretrain_downsampled_llm_6w.json   # 60,000 synthetic reaction diagrams
└── images_pretrain_resized/
    ├── single_line_resized/           # Single-line chain-style reactions
    ├── multi_line_resized/            # Multi-line chain-style reactions
    ├── branch_resized/                # Branching reactions
    └── cycle_resized/                 # Cyclic reactions

sft_data/
├── multi_task_sft_downsampled_llm.json # 190,800 multi-task SFT entries
├── images_train_aug_resized/          # Augmented training images
└── images_train_resized/              # Original resized training images

dpo_data/
└── train_downsampled_llm_dpo.json     # 14,169 DPO triplets (chosen/rejected pairs)
```

## Data Splits

| Split | Entries | Description |
|-------|---------|-------------|
| **Pretrain** | 60,000 | Synthetic reaction diagrams generated by LayoutDrivenSynthesizer (4 layout types: single-line, multi-line, branch, cycle) |
| **SFT** | 190,800 | Multi-task supervised fine-tuning data with 3 task variants: Vanilla Reaction Parsing (VRP), Region-Guided Reaction Parsing (RGRP), Prefix-Perturbed Reaction Parsing (PPRP) |
| **DPO** | 14,169 | Direct Preference Optimization triplets with chosen (ground-truth) and rejected (model prediction) annotations |

## Data Format

### Pretrain & SFT

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

### DPO

Each entry contains chosen/rejected pairs:

```json
{
    "messages": [{"from": "user", "value": "<image>\n..."}],
    "chosen": {"from": "assistant", "value": "<rxn>..."},
    "rejected": {"from": "assistant", "value": "<rxn>..."},
    "images": ["path/to/image.png"],
    "overall": {"precision": 0.8, "recall": 0.8, "f1": 0.8},
    "mol_only": {"precision": 0.9, "recall": 0.9, "f1": 0.9}
}
```

## Data Generation

- **Pretrain**: Synthetic data generated by [LayoutDrivenSynthesizer](https://github.com/jaydetang/RobustRDP/tree/main/pretrain_data_process) — renders molecules from PubChem SMILES onto reaction diagrams with 4 layout types.
- **SFT**: Built from [RxnLabelData](https://huggingface.co/datasets/Jingcz/RxnLabelData) with data augmentation (rotation, distortion, composite) and two auxiliary tasks (RGRP, PPRP). See [SFT data process](https://github.com/jaydetang/RobustRDP/tree/main/sft_data_process).
- **DPO**: Generated by running the SFT model on training data and filtering cases where model predictions (F1 < 0.8) differ from ground truth. See [DPO data process](https://github.com/jaydetang/RobustRDP/tree/main/dpo_data_process).

## Related Resources

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