OctMole: Multiscale 3D Molecular Generation with Hierarchical Spatial Flows
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Abstract (arXiv)
Generating accurate 3D molecules requires jointly determining a variable number of atoms, their identities, and geometry across spatial scales: global shape emerges coarsely, whereas chemical bonds demand fine local precision. Existing atom-based diffusion and flow models operate largely at a single scale, while dense spatial fields become costly at high resolution. We introduce OctMole, a multiscale octree flow framework for 3D molecular generation. A hierarchical occupancy flow progressively resolves sparse molecular support from coarse to fine, and a joint atom flow assigns atom types and continuous in-cell offsets to occupied leaves. This decomposition combines efficient global structure with subcell geometric precision, while cell corruption improves robustness to generated support. On QM9 and GEOM-DRUG, OctMole achieves strong chemical, distributional, and geometric quality, with particularly clear gains over Uni-3DAR on GEOM-DRUG and substantial efficiency gains over dense 3D generation. As an additional capability, intermediate occupancy states and selected regions provide spatial conditioning without task-specific retraining, supporting multiscale shape conditioning, regional editing, linker generation, and shape interpolation. Code and pretrained checkpoints are available at https://github.com/octree-nn/octmole and https://huggingface.co/Disembo/octmole, respectively.
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References · 23
- 2022Flow Matching for Generative Modelingcited by 5,702
- 2024Structured 3D Latents for Scalable and Versatile 3D Generationcited by 770
- 2022Equivariant Diffusion for Molecule Generation in 3Dcited by 677
- 2022DiffDock: Diffusion Steps, Twists, and Turns for Molecular Dockingcited by 313
- 2024Generative Flows on Discrete State-Spaces: Enabling Multimodal Flows with Applications to Protein Co-Designcited by 305
- 2020GEOM: Energy-annotated molecular conformations for property prediction and molecular generationcited by 243
- 2023Geometric Latent Diffusion Models for 3D Molecule Generationcited by 186
- 2022Equivariant 3D-Conditional Diffusion Models for Molecular Linker Designcited by 122
- 2023MiDi: Mixed Graph and 3D Denoising Diffusion for Molecule Generationcited by 98
- 2024OctFusion: Octree-based Diffusion Models for 3D Shape Generationcited by 43
- 2024SemlaFlow -- Efficient 3D Molecular Generation with Latent Attention and Equivariant Flow Matchingcited by 41
- 20233D molecule generation by denoising voxel gridscited by 40
11 more
- 2021Octree Transformer: Autoregressive 3D Shape Generation on Hierarchically Structured Sequencescited by 39
- 2023Trans-Dimensional Generative Modeling via Jump Diffusion Modelscited by 35
- 2025OctGPT: Octree-based Multiscale Autoregressive Models for 3D Shape Generationcited by 30
- 2024UniGEM: A Unified Approach to Generation and Property Prediction for Moleculescited by 21
- 2024ShEPhERD: Diffusing shape, electrostatics, and pharmacophores for bioisosteric drug designcited by 13
- 2025TABASCO: A Fast, Simplified Model for Molecular Generation with Improved Physical Qualitycited by 12
- 2025Unified Guidance for Geometry-Conditioned Molecular Generationcited by 9
- 2023Shape-conditioned 3D Molecule Generation via Equivariant Diffusion Modelscited by 8
- 2025Unified Cross-Scale 3D Generation and Understanding via Autoregressive Modelingcited by 8
- 2025Branching Flows: Discrete, Continuous, and Manifold Flow Matching with Splits and Deletionscited by 5
- 2026Zatom-1: Towards a Multimodal Foundation Model for 3D Molecules and Materialscited by 5
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