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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

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}
}