---
license: cc-by-4.0
task_categories:
- image-text-to-text
language:
- en
tags:
- chemistry
- supramolecular
- host-guest
- molecular-recognition
- visual-question-answering
pretty_name: 'SupraBench: Molecular Identification (VQA)'
configs:
- config_name: default
  data_files: identification.csv
---

# SupraBench: Molecular Identification (VQA)

Auxiliary **vision** task of [SupraBench](https://huggingface.co/SupraBench): given
the 2D depiction of a supramolecular host or guest, identify the molecule (its
name / alias set, and where available its canonical SMILES). It probes whether
multimodal LLMs can ground chemical structure from images alone.

## Links

- 📄 **Paper:** [`arXiv:2606.13477`](https://arxiv.org/abs/2606.13477)
- 💻 **Code:** https://github.com/Tianyi-Billy-Ma/SupraBench
- 🤗 **All datasets:** https://huggingface.co/SupraBench

## Contents

`identification.csv` indexes 1,777 molecule images stored under `images/`.

| column | description |
|---|---|
| `molecule_id` | integer id; image lives at `images/<molecule_id>.png` |
| `image` | relative path to the 2D depiction (`images/<id>.png`) |
| `role` | `host` or `guest` |
| `names_alias_set` | accepted name / alias set for the molecule |
| `cano_smiles` | canonical SMILES (empty where unresolved) |

## Usage

```python
from huggingface_hub import snapshot_download
import pandas as pd, os

root = snapshot_download("SupraBench/vqa", repo_type="dataset")
df = pd.read_csv(os.path.join(root, "identification.csv"))
row = df.iloc[0]
print(row["role"], row["names_alias_set"], row["cano_smiles"])
# image path: os.path.join(root, row["image"])
```

## Sources & license

Molecular structures use [PubChem](https://pubchem.ncbi.nlm.nih.gov/) and
[OPSIN](https://github.com/dan2097/opsin); binding records derive from
[SupraBank](https://suprabank.org/) (CC-BY-4.0). Released under CC-BY-4.0.

## Citation

```bibtex
@article{ma2026suprabench,
  title   = {SupraBench: A Benchmark for Supramolecular Host--Guest Chemistry Reasoning in Large Language Models},
  author  = {Ma, Tianyi and Ma, Yijun and Wang, Zehong and Sun, Weixiang and Li, Ziming and Schmidt, Connor R. and Zhang, Chuxu and Webber, Matthew J. and Ye, Yanfang},
  year    = {2026},
  eprint        = {2606.13477},
  archivePrefix = {arXiv},
  journal = {arXiv preprint arXiv:2606.13477}
}
```