fig4

Figure 4. The method of generating material structures by agents. (A) The overview of the MatAgent framework^[64]; (B) Pipeline for training and generation using the MolGPT model^[66]. Figure 4A is reproduced from “Accelerated Inorganic Materials Design with Generative AI Agents”, arXiv:2504.00741, under CC BY 4.0 license^[64]. Figure 4B is reproduced from “MolGPT: Molecular Generation Using a Transformer-Decoder Model”, J. Chem. Inf. Model. 2022, 62, 9, 2064-2076, with permission from American Chemical Society^[66]. LLM: Large language model; GNN: graph neural network; RDKiT: RDKit toolkit; LogP: the logarithm of the partition coefficient; TPSA: topological polar surface area; SAS: synthetic accessibility score; QED: quantitative estimate of drug-likeness; MolGPT: molecule generative pre-trained transformer.