Datasets:
Add dataset card: metadata, paper link, schema, usage (supersedes PR)
Browse files
README.md
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---
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license: cc-by-4.0
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task_categories:
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- image-text-to-text
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language:
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- en
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tags:
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- chemistry
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- supramolecular
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- host-guest
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- molecular-recognition
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- visual-question-answering
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pretty_name: 'SupraBench: Molecular Identification (VQA)'
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configs:
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- config_name: default
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data_files: identification.csv
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---
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# SupraBench: Molecular Identification (VQA)
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Auxiliary **vision** task of [SupraBench](https://huggingface.co/SupraBench): given
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the 2D depiction of a supramolecular host or guest, identify the molecule (its
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name / alias set, and where available its canonical SMILES). It probes whether
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multimodal LLMs can ground chemical structure from images alone.
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## Links
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- 📄 **Paper:** [`arXiv:2606.13477`](https://arxiv.org/abs/2606.13477)
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- 💻 **Code:** https://github.com/Tianyi-Billy-Ma/SupraBench
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- 🤗 **All datasets:** https://huggingface.co/SupraBench
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## Contents
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`identification.csv` indexes 1,777 molecule images stored under `images/`.
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| column | description |
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|---|---|
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| `molecule_id` | integer id; image lives at `images/<molecule_id>.png` |
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| `image` | relative path to the 2D depiction (`images/<id>.png`) |
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| `role` | `host` or `guest` |
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| `names_alias_set` | accepted name / alias set for the molecule |
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| `cano_smiles` | canonical SMILES (empty where unresolved) |
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## Usage
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```python
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from huggingface_hub import snapshot_download
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import pandas as pd, os
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root = snapshot_download("SupraBench/vqa", repo_type="dataset")
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df = pd.read_csv(os.path.join(root, "identification.csv"))
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row = df.iloc[0]
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print(row["role"], row["names_alias_set"], row["cano_smiles"])
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# image path: os.path.join(root, row["image"])
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```
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## Sources & license
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Molecular structures use [PubChem](https://pubchem.ncbi.nlm.nih.gov/) and
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[OPSIN](https://github.com/dan2097/opsin); binding records derive from
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[SupraBank](https://suprabank.org/) (CC-BY-4.0). Released under CC-BY-4.0.
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## Citation
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```bibtex
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@article{ma2026suprabench,
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title = {SupraBench: A Benchmark for Supramolecular Host--Guest Chemistry Reasoning in Large Language Models},
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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},
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year = {2026},
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eprint = {2606.13477},
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archivePrefix = {arXiv},
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journal = {arXiv preprint arXiv:2606.13477}
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}
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```
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