Papers › A Bayesian Flow Network Framework for Chemistry Tasks
A Bayesian Flow Network Framework for Chemistry Tasks
Nianze Tao, Minori Abe
In this work, we introduce ChemBFN, a language model that handles chemistry tasks based on Bayesian flow networks working on discrete data. A new accuracy schedule is proposed to improve the sampling quality by significantly reducing the reconstruction loss. We show evidence that our method is appropriate for generating molecules with satisfied diversity even when a smaller number of sampling steps is used. A classifier-free guidance method is adapted for conditional generation. It is also worthwhile to point out that after generative training, our model can be fine-tuned on regression and classification tasks with the state-of-the-art performance, which opens the gate of building all-in-one models in a single module style. Our model has been open sourced at https://github.com/Augus1999/bayesian-flow-network-for-chemistry.
Code
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Molecular Property Prediction | BACE | ChemBFN | ROC-AUC | 73.56 | #15 of 20 | Archive leaderboard | report |
| Molecular Property Prediction | BBBP | ChemBFN | ROC-AUC | 95.74 | #2 of 29 | Archive leaderboard | report |
| Molecular Property Prediction | ESOL | ChemBFN | RMSE | 0.884 | #17 of 20 | Archive leaderboard | report |
| Molecular Property Prediction | FreeSolv | ChemBFN | RMSE | 1.418 | #11 of 22 | Archive leaderboard | report |
| Molecular Property Prediction | HIV | ChemBFN | ROC-AUC | 79.37 | #3 of 4 | Archive leaderboard | report |
| Molecular Property Prediction | HIV dataset | ChemBFN | AUC | 0.794 | #3 of 11 | Archive leaderboard | report |
| Molecular Property Prediction | Lipophilicity | ChemBFN | RMSE | 0.746 | #7 of 13 | Archive leaderboard | report |
| Molecular Property Prediction | clintox | ChemBFN | ROC-AUC | 99.18 | #2 of 20 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
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