Atomistic Language Models Understand and Generate Materials

Atomistic Language Models (ALMs) unify language and atomistic structures, enabling natural language-driven crystal generation and optimization. ALMs use a continuous bridge to map language embeddings into atomistic diffusion steering space and employ Text-to-Crystal Feynman-Kac for stoichiometric accuracy. The ALM Bench benchmark evaluates text-conditioned material generation and optimization, with code and weights to be released soon.