| --- |
| pretty_name: ChemRxn-Bench (RxnMiner Benchmark) |
| license: cc-by-nc-sa-4.0 |
| language: |
| - en |
| tags: |
| - chemistry |
| - reaction-extraction |
| - optical-chemical-structure-recognition |
| - multimodal |
| - benchmark |
| task_categories: |
| - image-to-text |
| size_categories: |
| - n<1K |
| configs: |
| - config_name: default |
| data_files: |
| - split: test |
| path: data/test-*.parquet |
| extra_gated_heading: Request access to ChemRxn-Bench |
| extra_gated_description: >- |
| The figures come from published articles and remain the property of their publishers. Access is granted for |
| non-commercial research after review by the dataset maintainers. |
| extra_gated_button_content: Submit request |
| extra_gated_fields: |
| Full name: text |
| Affiliation: text |
| Email (institutional): text |
| Intended use: text |
| I will use this dataset only for non-commercial research under its CC BY-NC-SA license: checkbox |
| I will cite the RxnMiner paper in work that uses this dataset: checkbox |
| --- |
| |
| # ChemRxn-Bench |
|
|
| <p align="center"> |
| 🚀 <a href="https://rxnminer.github.io/RxnMiner/benchmark/">Benchmark</a> | |
| 💻 <a href="https://github.com/rxnminer/RxnMiner">GitHub</a> | |
| 📄 <a href="https://huggingface.co/papers/2611.02826">Paper</a> |
| </p> |
|
|
|
|
| A benchmark for extracting **complete, structured chemical reactions from literature figures**: reaction schemes, |
| substrate-scope tables with R-group templates, condition-optimization tables, multistep routes and total syntheses. |
| Each figure comes with a manually annotated and expert-reviewed reference answer listing every concrete reaction drawn or |
| implied in the figure, with exact molecular identities (SMILES, stereochemistry included), conditions and yields. |
|
|
| It accompanies the paper *RxnMiner: A Multimodal Agent for Structured Reaction Data Extraction from Chemistry |
| Figures* ([arXiv:2611.02826](https://arxiv.org/abs/2611.02826)). Code: [github.com/rxnminer/RxnMiner](https://github.com/rxnminer/RxnMiner). |
| The silver reaction corpus extracted by RxnMiner is released as [UniParser/RxnMiner-Dataset](https://huggingface.co/datasets/UniParser/RxnMiner-Dataset). |
|
|
| | | | |
| |---|---| |
| | Figures | 603 | |
| | Concrete reactions | 8,510 (8,547 annotated records before the scorer's normalisation) | |
| | Generic templates (not scored) | 675 | |
| | Layouts | substrate scope 425, table 161, single step 6, complex figure 6, multistep / total synthesis 5 | |
| | Difficulty | Very Hard 435, Hard 37, Medium 25, Easy 28, Very Easy 78 | |
|
|
| ## Data fields |
|
|
| | Field | Type | Description | |
| |---|---|---| |
| | `id` | string | Figure id (stable across releases) | |
| | `image` | image | The figure, including its caption, table text and footnotes; the only model input | |
| | `annotation` | string (JSON) | Reference answer in the unified JSON format (below) | |
| | `layout_type` | string | `substrate_scope`, `table`, `single_step`, `complex_figure`, `multistep_or_total_synthesis` | |
| | `difficulty` | string | Difficulty tier, defined by how well Qwen3.8-Flash-Next performs on the figure (see the paper) | |
| | `num_reactions` | int | Concrete reactions in `annotation.selected_examples` | |
| | `num_templates` | int | Generic templates in `annotation.reaction_templates` (never scored) | |
| | `source` | string | Journal the figure was published in, or the public dataset it was collected from (ChemEAGLE, OpenChemIE) | |
|
|
| ## Unified JSON (reference answer and expected prediction format) |
|
|
| ```json |
| { |
| "reaction_templates": [ ... generic schemes with R groups (not scored) ... ], |
| "selected_examples": [ |
| { |
| "instance_id": "3a", |
| "reactants": [{"identifier": "1a", "smiles": "...", "bbox": [x0, y0, x1, y1]}], |
| "products": [{"identifier": "3a", "smiles": "..."}], |
| "conditions": [[{"role": "catalyst", "text": "Pd(PPh3)4 (5 mol%)"}, {"role": "solvent", "text": "THF"}]], |
| "metrics": [{"role": "yield", "text": "82%"}] |
| } |
| ] |
| } |
| ``` |
|
|
| In the reference answers, molecules store their structure as `E-SMILES` (MolParser extended SMILES) or `SMILES`; |
| predictions may use `smiles`, `E-SMILES` or `SMILES` (the scorer reads them in that order). Reagents printed over an |
| arrow are recorded as condition text. Multistep routes list their stages under `steps`. Other fields in the reference |
| answers (descriptions, footnotes, notes on conditions) document where each value comes from in the figure and are not |
| scored. |
|
|
| ## Evaluation |
|
|
| The scorer is `scorer/score_reaction_strict.py` in this repository. It requires `rdkit==2022.9.5`; other RDKit |
| versions can change canonical SMILES and therefore scores. |
|
|
| ```python |
| import importlib.util, json |
| from datasets import load_dataset |
| from huggingface_hub import hf_hub_download |
| |
| path = hf_hub_download("UniParser/RxnMiner-Benchmark", "scorer/score_reaction_strict.py", repo_type="dataset") |
| spec = importlib.util.spec_from_file_location("score_reaction_strict", path) |
| S = importlib.util.module_from_spec(spec) |
| spec.loader.exec_module(S) |
| |
| ds = load_dataset("UniParser/RxnMiner-Benchmark", split="test") |
| row = ds[0] |
| prediction = {...} # your system's unified JSON for row["image"] |
| result = S.score_both(prediction, json.loads(row["annotation"])) |
| print(result["reaction_f1_iso"]) # stereochemistry-aware; reaction_f1_ns ignores stereochemistry |
| ``` |
|
|
| From the root of a local copy of this repository: `python scorer/score_reaction_strict.py prediction.json reference.json`. |
|
|
| The concrete reactions in `selected_examples` are scored; each step of a multistep route counts as a separate |
| reaction, and generic templates in `reaction_templates` are not scored. **Reaction recall** = fraction of reference |
| products recovered; **reaction precision** = predicted reactions whose reactant set and product set both match a |
| reference reaction exactly (after RDKit canonicalisation), divided by all predicted reactions; **reaction F1** is |
| computed per figure and averaged over figures (macro). A failed or missing prediction scores 0 and stays in the |
| denominator. In the paper, RxnMiner with Qwen3.8-Flash-Next reaches 71.0 macro reaction F1 (stereochemistry-aware), |
| versus 21.0 for the same model prompted directly. |
|
|
| ## License and use |
|
|
| The dataset is released under [CC BY-NC-SA 4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/): non-commercial |
| use, with attribution, and derivatives under the same license. The figures are reproduced from published articles for |
| non-commercial research and remain the property of their publishers. Access requests are reviewed by the maintainers. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @misc{hu2026rxnminer, |
| title = {RxnMiner: A Multimodal Agent for Structured Reaction Data Extraction from Chemistry Figures}, |
| author = {Hu, Jinbo and Zhang, Songren and Fu, Chuanxun and Huang, Jinrui and Wong, Zhen Hao and Cui, Dongxu and |
| Fan, Haoran and Ge, Muhao and Jian, Zhen and Zhou, Jian and Luo, Chengxiang and Lyu, Han and Tao, Haoyi and |
| Huang, Chaozheng and Li, Hanzheng and Wang, ZiChen and Ma, Hengtian and Dai, Jinyang and Wang, Nan and |
| Hong, Yanhui and Fang, Xi and Ke, Guolin}, |
| year = {2026}, |
| eprint = {2611.02826}, |
| archivePrefix = {arXiv}, |
| url = {https://arxiv.org/abs/2611.02826} |
| } |
| ``` |
|
|
