@askalphaxiv: "Atomistic Language Models Understand and Generate Materials" Most materials AI still treats crystals and language sepa…
Summary
This paper introduces an atomistic language model that integrates a 3D atom encoder, Qwen LLM, and diffusion crystal generator to natively handle multimodal materials data, achieving state-of-the-art crystal structure prediction and de novo generation.
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Cached at: 06/24/26, 06:28 PM
“Atomistic Language Models Understand and Generate Materials”
Most materials AI still treats crystals and language separately, either turning atoms into lossy text formats or making LLMs call atomistic tools.
This paper makes materials natively multimodal by connecting a 3D atom encoder, Qwen LLM, and diffusion crystal generator through continuous latent projectors.
This model can read atomic coordinates, predict properties, edit crystals from text, and generate stable new materials, with SoTA crystal structure prediction and strong de novo generation.
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