Beyond CLMs, graph neural networks have been proposed specifically for the purpose of being able to conduct both unconstrained and scaffold constrained generation with MoLeR . New language-based molecular representations have also been proposed to offer greater flexibility in conducting constrained molecule generation. Further exemplifying the importance and utility of flexibly conducting constrained or unconstrained molecule generation with the same model for drug design.