Datasets:
metadata
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: 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 - 💻 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
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 and OPSIN; binding records derive from SupraBank (CC-BY-4.0). Released under CC-BY-4.0.
Citation
@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}
}