| | --- |
| | license: mit |
| | language: |
| | - en |
| | tags: |
| | - chemistry |
| | - biology |
| | size_categories: |
| | - 1K<n<10K |
| | --- |
| | |
| | # Tasks |
| | ## mol_und |
| | - fg-level |
| | - `fg_count.json` |
| | - 100 samples across 38 different functional groups detection |
| | - `ring_count.json` |
| | - 20 samples, 9 types of ring unit |
| | - scaffold-level |
| | - `Murcko_scaffold.json` |
| | - 40 samples, using MurckoScaffold extraction |
| | - `ring_system_scaffold.json` |
| | - 60 samples, extract ring system as scaffolds |
| | - SMILES-level |
| | - `equivalence.json` |
| | - 50 samples, each smiles -> mutate -> permutate, mutated smiles differs from original smiles |
| | - 50 samples, each smiles -> permutate, permutated smiles is same with original smiles |
| |
|
| | ## mol_edit |
| | - `add.json` |
| | - 20 samples, covers 10 func groups addition |
| | - `delete.json` |
| | - 20 samples, covers 10 func groups deletion |
| | - `sub.json` |
| | - 60 samples, covers 37 func groups substitution |
| | |
| | ## mol_opt |
| | - `drd.json` |
| | - 100 samples, target-level |
| | - `gsk.json` |
| | - 100 samples, target-level |
| | - `jnk.json` |
| | - 100 samples, target-level |
| | - `logp.json` |
| | - 100 samples, physicochemical-level |
| | - `qed.json` |
| | - 100 samples, physicochemical-level |
| | - `solubility.json` |
| | - 100 samples, physicochemical-level |
| |
|
| | ## reaction |
| | - forward reaction prediction |
| | - `fs.json` |
| | - 100 samples, 100 rxn-cls (each has one sample) |
| | - (single-step) retrosynthesis prediction |
| | - `retro.json` |
| | - 100 samples, 100 rxn-cls (each has one sample) |
| | - reaction condition prediction/recommendation |
| | - `rcr.json` |
| | - 90 samples. 10 types of reaction. Each type has 3 samples for 'Catalyst' prediction, 3 for 'Reagent' prediction and 3 for 'Solvent' prediction |
| | - Next elementary step product prediction (NEPP) |
| | - `nepp.json` |
| | - given former elementary steps description, predict next elementary step's product. |
| | - 85 rxn cls, each has 1 sample |
| | - Mechanism Route Selection (MechSel) |
| | - `mechsel.json` |
| | - 100 samples |
| | |
| | # Links |
| | - Our larger CoT dataset [ChemCoTBench-CoT](https://huggingface.co/datasets/OpenMol/ChemCoTBench-CoT) |
| |
|
| | # Citation |
| | If you find our work helpful, feel free to give us a cite. |
| | ``` |
| | @article{li2025chemicalqaevaluatingllms, |
| | title={Beyond Chemical QA: Evaluating LLM's Chemical Reasoning with Modular Chemical Operations}, |
| | author={Hao Li and He Cao and Bin Feng and Yanjun Shao and Xiangru Tang and Zhiyuan Yan and Li Yuan and Yonghong Tian and Yu Li}, |
| | year={2025}, |
| | eprint={2505.21318}, |
| | archivePrefix={arXiv}, |
| | primaryClass={cs.AI}, |
| | url={https://arxiv.org/abs/2505.21318}, |
| | } |
| | ``` |
