---
language:
- en
pretty_name: ToBAC
size_categories:
- n<1K
task_categories:
- text-to-image
- image-to-text
tags:
- multimodal
- backdoor
- robustness
configs:
- config_name: default
  data_files:
  - split: train
    path: data/*.parquet
---

# ToBAC

Paired clean and concept-edited images accompanying
[Token by Token, Compromised: Backdoor Vulnerabilities in Unified Autoregressive Models](https://arxiv.org/abs/2605.19227),
accepted at NeurIPS 2026. [Code](https://github.com/multimodal-ai-lab/ToBAC).

## Format

One configuration, with **500 rows** in the `train` split, indexed **0–499**.
Each row contains a context and four images, for **2,000 images** in total.

| Column | Type | Description |
| --- | --- | --- |
| `context` | string | Prompt template containing `{}` |
| `clean` | Image | Clean image |
| `rainbow` | Image | Rainbow-flag variant |
| `anarchy` | Image | Anarchy-symbol variant |
| `pear` | Image | Pear-logo variant |

## Loading

```python
from datasets import load_dataset

dataset = load_dataset("MAI-Lab/ToBAC", split="train")
example = dataset[0]
print(example["context"])
example["clean"].show()
example["pear"].show()
```

## Data creation

Edited images were generated from the clean image and a concept reference with
`diffusers/FLUX.2-dev-bnb-4bit`, revision
`c30ad107542e63f222f864a8de510204394fb18a`, using 50 inference steps,
guidance 4.0, and seed 42 for each image.

## Intended use

ToBAC supports research on multimodal model robustness and backdoor defenses.

## License

No dataset license has been specified. The code license does not automatically
apply to these images.