Hierarchy-Guided Topology Latent Flow for Molecular Graph Generation
Generating chemically valid 3D molecules is hindered by discrete bond topology: small local bond errors can cause global failures (valence violations, disconnections, implausible rings), especially for drug-like molecules with long-range constraints. Many unconditional 3D generators emphasize coordinates and then infer bonds or rely on post-processing, leaving topology feasibility weakly controlled. We propose Hierarchy-Guided Latent Topology Flow (HLTF), a planner-executor model that generates bond graphs with 3D coordinates, using a latent multi-scale plan for global context and a constraint-aware sampler to suppress topology-driven failures. On QM9, HLTF achieves 98.8% atom stability a...
| Authors | Urvi Awasthi, Alexander Arjun Lobo, Leonid Zhukov |
|---|---|
| Primary category | cs.LG |
| Published | 28 March 2026 |
| Last updated at source | 28 March 2026 |
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