AI RESEARCH
Controllable Molecular Generative Foundation Models
arXiv CS.LG
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ArXi:2605.15354v1 Announce Type: new Despite the success of foundation models in language and vision, molecular graph generation still lacks a unified framework for heterogeneous design tasks with reliable controllability. While reinforcement learning (RL) offers a natural post-