---
license: cc-by-4.0
language:
  - en
tags:
  - circuit-diagrams
  - document-understanding
  - graph-recovery
  - connectivity-verification
  - vision-language-models
  - digital-logic
size_categories:
  - 1K<n<10K
pretty_name: LogicBench-1K
---

# LogicBench-1K

Digital logic circuit diagrams with topology-level ground-truth graph annotations.

**Official repository:** [github.com/tkcl-research/LogicBench1k](https://github.com/tkcl-research/LogicBench1k)

## Paper

> **Stroke-Level Connectivity Verification: Grounding Vision-Language Models Against Topology Hallucination in Diagram Understanding**  
> Abdullah Ibne Hanif Arean, Niamul Hassan Samin, Md Arifur Rahman, Renu Akter Suity, Juena Ahmed Noshin, and Md Ashikur Rahman  
> *International Conference on Document Analysis and Recognition (ICDAR), 2026*

## Dataset summary

| Property | Value |
|----------|-------|
| Samples | 1,000 |
| Image format | JPEG, 512x512 px |
| Annotation format | JSON (directed graph per image) |
| Train / Val / Test | 700 / 100 / 200 |
| Gate vocabulary | AND, OR, NOT, NAND, NOR, XOR, XNOR |
| Total gates / edges | 6,174 / 6,423 |

## Dataset structure

```
LogicBench-1K/
├── images/
├── annotations/
│   └── splits/
├── metadata/
└── schema/
```

## Splits

| Split | File | Count | Sample ID range |
|-------|------|-------|-----------------|
| Test | `annotations/splits/test.txt` | 200 | lb1k_00000-lb1k_00199 |
| Train | `annotations/splits/train.txt` | 700 | lb1k_00200-lb1k_00899 |
| Validation | `annotations/splits/val.txt` | 100 | lb1k_00900-lb1k_00999 |

## Load a sample

```python
import json
from huggingface_hub import hf_hub_download

sample_id = "lb1k_00042"
ann_path = hf_hub_download("TKCL-HF/LogicBench-1K", f"annotations/{sample_id}.json", repo_type="dataset")
img_path = hf_hub_download("TKCL-HF/LogicBench-1K", f"images/{sample_id}.jpg", repo_type="dataset")

with open(ann_path) as f:
    graph = json.load(f)
```

## Citation

If you use LogicBench-1K, please cite:

> **Stroke-Level Connectivity Verification: Grounding Vision-Language Models Against Topology Hallucination in Diagram Understanding**  
> Abdullah Ibne Hanif Arean, Niamul Hassan Samin, Md Arifur Rahman, Renu Akter Suity, Juena Ahmed Noshin, and Md Ashikur Rahman  
> *International Conference on Document Analysis and Recognition (ICDAR), 2026*

```bibtex
@inproceedings{arean2026slcv,
  author    = {{Abdullah Ibne Hanif Arean} and {Niamul Hassan Samin} and {Md Arifur Rahman} and {Renu Akter Suity} and {Juena Ahmed Noshin} and {Md Ashikur Rahman}},
  title     = {Stroke-Level Connectivity Verification: Grounding Vision-Language Models Against Topology Hallucination in Diagram Understanding},
  booktitle = {International Conference on Document Analysis and Recognition (ICDAR)},
  year      = {2026}
}
```

## License

[Creative Commons Attribution 4.0 International (CC BY 4.0)](https://creativecommons.org/licenses/by/4.0/)