MOSA: Molecular Subspace Assembly for Unified Molecular Generation and Editing

Molecular design often requires both generating new molecules from multiple property specifications and editing existing molecules while preserving their underlying structures. Although these tasks are closely related, conventional joint adaptation can benefit one task while degrading the other. We introduce $\text{MOSA (Molecular Subspace Assembly)}$, a unified adapter for a frozen language model that organizes low-rank updates into shared, generation-private, and editing-private subspaces. A permutation-invariant property controller uses individual conditions and their pairwise interactions to modulate the shared update. For editing, a source controller combines the input molecule with the requested properties to scale and shift the editing-specific update. The same frozen backbone and text interface serve both tasks, while each request changes the adaptation applied to hidden states. At 39,500 updates, MOSA achieves $\text{60.45\%}$ strict de novo success on 6,000 common requests versus SketchMol's 54.5% under native training budgets, and $\text{76.98\%}$ strict editing success on 5,000 requests. At matched one-pass exposure, MOSA improves both tasks over a conventional joint adapter and avoids the editing-side negative transfer observed relative to the editing specialist.