Datasets:
File size: 5,603 Bytes
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license: cc-by-4.0
task_categories:
- question-answering
language:
- en
tags:
- chemistry
- solubility
- cheminformatics
- llm-benchmark
- smiles
pretty_name: SoluBench
configs:
- config_name: task1
data_files:
- split: test
path: task1_pairwise_solvent_comparison.csv
- config_name: task2
data_files:
- split: test
path: task2_best_solvent_selection.csv
- config_name: task3
data_files:
- split: test
path: task3_cosolvent_effect_prediction.csv
- config_name: task4
data_files:
- split: test
path: task4_pairwise_compound_comparison.csv
---
# SoluBench
**SoluBench** is a benchmark for evaluating large language models on solubility-related tasks of various complexity. It is built on top of [BigSolDB v2.0](https://www.nature.com/articles/s41597-025-05559-8) and [MixtureSolDB](https://doi.org/10.26434/chemrxiv-2025-m51v8) — two curated experimental solubility datasets.
> 📄 Preprint: *coming soon*
> 💻 GitHub: [levakrasnovs/SoluBench](https://github.com/levakrasnovs/SoluBench)
---
## Tasks
| Config | Task | Description | Input | Output | n | Random baseline |
|--------|------|-------------|-------|--------|---|-----------------|
| `task1` | Pairwise solvent comparison | Given a compound (SMILES) and two solvents, select the one with higher solubility | SMILES + 2 solvents | A / B | 3699 | 50.0% |
| `task2` | Best solvent selection | Given a compound and a list of solvents, select the one with highest solubility | SMILES + N solvents | letter | — | ~17.1% |
| `task3` | Co-solvent effect prediction | Given a compound, a base solvent and a co-solvent mixture, predict whether solubility increases or decreases | SMILES + mixture composition | A / B | — | ~16.7% |
| `task4` | Pairwise compound comparison | Given a solvent and two compounds (SMILES), select the one with higher solubility | Solvent + 2 SMILES | A / B | 3000 | 50.0% |
---
## Usage
```python
from datasets import load_dataset
# Load a specific task
ds = load_dataset("levakrasnovs/SoluBench", "task1")
print(ds["test"][0])
# Load all tasks
for task in ["task1", "task2", "task3", "task4"]:
ds = load_dataset("levakrasnovs/SoluBench", task)
print(f"{task}: {len(ds['test'])} rows")
```
---
## Data fields
### Task 1 — Pairwise solvent comparison
| Field | Description |
|-------|-------------|
| `id` | Unique row identifier |
| `DOI` | Source publication |
| `SMILES` | Compound SMILES |
| `Temperature_K` | Temperature in Kelvin |
| `Solvent_A` | First solvent |
| `Solvent_B` | Second solvent |
| `LogS_A` | Experimental log solubility in solvent A (mol/L) |
| `LogS_B` | Experimental log solubility in solvent B (mol/L) |
| `Delta_LogS` | \|LogS_A − LogS_B\| |
| `Answer` | Correct answer (A or B) |
### Task 2 — Best solvent selection
| Field | Description |
|-------|-------------|
| `id` | Unique row identifier |
| `DOI` | Source publication |
| `SMILES` | Compound SMILES |
| `Temperature_K` | Temperature in Kelvin |
| `Best_solvent` | Solvent with highest solubility |
| `Best_LogS` | LogS in best solvent |
| `Second_best_solvent` | Solvent with second highest solubility |
| `Second_best_LogS` | LogS in second best solvent |
| `Delta_LogS_best_minus_second` | LogS difference between best and second best |
| `All_solvents` | Semicolon-separated list of all solvents |
| `All_LogS` | Semicolon-separated list of all LogS values |
| `Answer` | Correct answer (letter corresponding to best solvent) |
### Task 3 — Co-solvent effect prediction
| Field | Description |
|-------|-------------|
| `id` | Unique row identifier |
| `DOI` | Source publication |
| `SMILES` | Compound SMILES |
| `Temperature_K` | Temperature in Kelvin |
| `Base_solvent` | Pure base solvent |
| `Added_solvent` | Co-solvent added to the mixture |
| `Fraction_base` | Fraction of base solvent |
| `Fraction_added` | Fraction of added co-solvent |
| `New_composition` | Human-readable mixture description |
| `Fraction_type` | Type of fraction (mole/volume/mass) |
| `Delta_LogS_new_minus_base` | LogS(mixture) − LogS(pure base) |
| `Answer` | A = solubility enhanced, B = solubility reduced |
### Task 4 — Pairwise compound comparison
| Field | Description |
|-------|-------------|
| `id` | Unique row identifier |
| `Solvent` | Solvent name |
| `Temperature_K` | Temperature in Kelvin |
| `SMILES_A` | SMILES of compound A |
| `SMILES_B` | SMILES of compound B |
| `Compound_name_A` | Name of compound A |
| `Compound_name_B` | Name of compound B |
| `LogS_A` | Experimental log solubility of compound A (mol/L) |
| `LogS_B` | Experimental log solubility of compound B (mol/L) |
| `DOI_A` | Source publication for compound A |
| `DOI_B` | Source publication for compound B |
| `delta_logS` | LogS_A − LogS_B |
| `Answer` | Correct answer (A or B) |
---
## Source datasets
| Dataset | Paper | Download |
|---------|-------|----------|
| BigSolDB v2.0 | [Nature Scientific Data](https://www.nature.com/articles/s41597-025-05559-8) | [Zenodo](https://doi.org/10.5281/zenodo.15094979) |
| MixtureSolDB | [ChemRxiv](https://doi.org/10.26434/chemrxiv-2025-m51v8) | [Zenodo](https://doi.org/10.5281/zenodo.18660057) |
---
## Model results
Full model evaluation results (20+ LLMs including GPT, Claude, Gemini, Grok, Qwen, DeepSeek, GLM) are available in the [GitHub repository](https://github.com/levakrasnovs/SoluBench/tree/main/results).
---
## Citation
> Citation will be added upon preprint publication.
---
## License
[CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) |