3 papers
physics.chem-ph2026
Harnessing AtomisticSkills for Agentic Atomistic Research
Bowen Deng, Bohan Li, Matthew Cox +20
Computational materials science and chemistry span vast knowledge domains and fractured software ecosystems. Although large language models (LLMs) have demonstrated research capabi…
cs.LG2026
Zatom-1: Towards a Multimodal Foundation Model for 3D Molecules and Materials
Alex Morehead, Miruna Cretu, Antonia Panescu +14
General-purpose 3D modeling in chemistry encompasses molecules and materials, requiring both generative and predictive capabilities. However, most existing AI approaches are optimi…
cs.LG2026
Self-Conditioned Denoising for Atomistic Representation Learning
Tynan Perez, Rafael Gomez-Bombarelli
The success of large-scale pretraining in NLP and computer vision has catalyzed growing efforts to develop analogous foundation models for the physical sciences. However, pretraini…