AI RESEARCH
MolPIF: A Parameter Interpolation Flow Model for Molecule Generation
arXiv CS.LG
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ArXi:2507.13762v4 Announce Type: replace Motivation: Structure-based drug design (SBDD) has advanced with deep generative models, but bridging the gap between continuous atomic coordinates and discrete atom types remains a challenge. Current approaches, such as diffusion and flow matching models, often fail to unify these heterogeneous modalities, relying on separate strategies or ill-fitting Euclidean metrics for discrete variables. This lack of a consistent framework limits generative models' ability to capture the geometric and chemical structure of protein-ligand complexes.