| --- |
| license: apache-2.0 |
| language: |
| - en |
| configs: |
| - config_name: MolCustom_AtomNum |
| data_files: |
| - split: test |
| path: "MolCustom_AtomNum.csv" |
| - config_name: MolCustom_BondNum |
| data_files: |
| - split: test |
| path: "MolCustom_BondNum.csv" |
| - config_name: MolCustom_FunctionalGroup |
| data_files: |
| - split: test |
| path: "MolCustom_FunctionalGroup.csv" |
| - config_name: MolEdit_AddComponent |
| data_files: |
| - split: test |
| path: "MolEdit_AddComponent.csv" |
| - config_name: MolEdit_SubComponent |
| data_files: |
| - split: test |
| path: "MolEdit_SubComponent.csv" |
| - config_name: MolEdit_DelComponent |
| data_files: |
| - split: test |
| path: "MolEdit_DelComponent.csv" |
| - config_name: MolOpt_LogP |
| data_files: |
| - split: test |
| path: "MolOpt_LogP.csv" |
| - config_name: MolOpt_MR |
| data_files: |
| - split: test |
| path: "MolOpt_MR.csv" |
| - config_name: MolOpt_QED |
| data_files: |
| - split: test |
| path: "MolOpt_QED.csv" |
| --- |
| |
| # S^2-Bench Dataset (TOMG) (full version, 45k entries) |
| Official Huggingface Datasets for [S^2-Bench](https://phenixace.github.io/tomgbench/): *"Speak-to-Structure: Evaluating LLMs in Open-domain Natural Language-Driven Molecule Generation"* |
|
|
| Please refer to our [Github Repo](https://github.com/phenixace/S2-TOMG-Bench) for more usage and useful information. |
|
|
| ## Configurations |
|
|
| Each configuration represents a different task: |
|
|
| - **MolCustom_AtomNum**: Molecular customized generation by atom number |
| - **MolCustom_BondNum**: Molecular customized generation by bond number |
| - **MolCustom_FunctionalGroup**: Molecular customized generation by functional group |
| - **MolEdit_AddComponent**: Molecular editing - adding components |
| - **MolEdit_SubComponent**: Molecular editing - substituting components |
| - **MolEdit_DelComponent**: Molecular editing - deleting components |
| - **MolOpt_LogP**: Molecular optimization for LogP |
| - **MolOpt_MR**: Molecular optimization for MR |
| - **MolOpt_QED**: Molecular optimization for QED |
| |
| ## Usage |
| |
| ```python |
| from datasets import load_dataset |
| |
| # Load a specific configuration |
| dataset = load_dataset("phenixace/S2-TOMG-Bench", "MolCustom_AtomNum") |
| |
| # Or load all configurations |
| configs = ["MolCustom_AtomNum", "MolCustom_BondNum", "MolCustom_FunctionalGroup", |
| "MolEdit_AddComponent", "MolEdit_SubComponent", "MolEdit_DelComponent", |
| "MolOpt_LogP", "MolOpt_MR", "MolOpt_QED"] |
| |
| datasets = {config: load_dataset("phenixace/S2-TOMG-Bench", config) for config in configs} |
| ``` |
| |
| ## Citation |
| If you use our data, please cite us in the format below: |
| ```bibtex |
| @article{li2024speak, |
| title={Speak-to-Structure: Evaluating LLMs in Open-domain Natural Language-Driven Molecule Generation}, |
| author={Li, Jiatong and Li, Junxian and Liu, Yunqing and Zheng, Changmeng and Wei, Xiaoyong and Zhou, Dongzhan and Li, Qing}, |
| journal={arXiv preprint arXiv:2412.14642v3}, |
| year={2024} |
| } |
| ``` |
| |
| |
| ## Current Leaderboard |
| |
| | Rank | Model | \#Parameters (B) | $\overline{S\!R}$ (\%) | $\overline{W\!S\!R} (\%)$ | | |
| |------|-----------------------------------------------------|------------------|------------------------|---------------------------|---| |
| | 1 | Llama3.1-8B (OpenMolIns-xlarge) | 8 | 58.79 | 39.33 | | |
| | 2 | Claude-3.5 | - | 51.10 | 35.92 | | |
| | 3 | Gemini-1.5-pro | - | 52.25 | 34.80 | | |
| | 4 | GPT-4-turbo | - | 50.74 | 34.23 | | |
| | 5 | GPT-4o | - | 49.08 | 32.29 | | |
| | 6 | Claude-3 | - | 46.14 | 30.47 | | |
| | 7 | Llama3.1-8B (OpenMolIns-large) | 8 | 43.1 | 27.22 | | |
| | 8 | Galactica-125M (OpenMolIns-xlarge) | 0.125 | 44.48 | 25.73 | | |
| | 9 | Llama3-70B-Instruct (Int4) | 70 | 38.54 | 23.93 | | |
| | 10 | Galactica-125M (OpenMolIns-large) | 0.125 | 39.28 | 23.42 | | |
| | 11 | Galactica-125M (OpenMolIns-medium) | 0.125 | 34.54 | 19.89 | | |
| | 12 | GPT-3.5-turbo | - | 28.93 | 18.58 | | |
| | 13 | Galactica-125M (OpenMolIns-small) | 0.125 | 24.17 | 15.18 | | |
| | 14 | Gemma3-12B | 12 | 26.28 | 15.00 | | |
| | 15 | Deepseek-R1-distill-Qwen-7B | 7 | 25.07 | 14.61 | | |
| | 16 | Llama3.1-8B-Instruct | 8 | 26.26 | 14.09 | | |
| | 17 | Llama3-8B-Instruct | 8 | 26.40 | 13.75 | | |
| | 18 | chatglm-9B | 9 | 18.50 | 13.13(7) | | |
| | 19 | Galactica-125M (OpenMolIns-light) | 0.125 | 20.95 | 13.13(6) | | |
| | 20 | ChemDFM-v1.5-8B | 8 | 18.24 | 12.07 | | |
| | 21 | ChemLLM-20B | 20 | 16.23 | 9.76 | | |
| | 22 | Llama3.2-1B (OpenMolIns-large) | 1 | 14.11 | 8.10 | | |
| | 23 | yi-1.5-9B | 9 | 14.10 | 7.32 | | |
| | 24 | Mistral-7B-Instruct-v0.2 | 7 | 11.17 | 4.81 | | |
| | 25 | BioT5-base | 0.25 | 24.19 | 4.21 | | |
| | 26 | MolT5-large | 0.78 | 23.11 | 2.89 | | |
| | 27 | Llama3.1-1B-Instruct | 1 | 3.95 | 1.99 | | |
| | 28 | MolT5-base | 0.25 | 11.11 | 1.30(0) | | |
| | 29 | MolT5-small | 0.08 | 11.55 | 1.29(9) | | |
| | 30 | Qwen2-7B-Instruct | 7 | 0.18 | 0.15 | | |
| |
| ## OpenMolIns |
| |
| The instruction tuning datasets are also available at Hugging Face Datasets: |
| |
| 1. [OpenMolIns-light](https://huggingface.co/datasets/phenixace/OpenMolIns-light) |
| 2. [OpenMolIns-small](https://huggingface.co/datasets/phenixace/OpenMolIns-small) |
| 3. [OpenMolIns-medium](https://huggingface.co/datasets/phenixace/OpenMolIns-medium) |
| 4. [OpenMolIns-large](https://huggingface.co/datasets/phenixace/OpenMolIns-large) |
| 5. [OpenMolIns-xlarge](https://huggingface.co/datasets/phenixace/OpenMolIns-xlarge) |
| |
| |
