collaborators

5 papers

cond-mat.mtrl-sci2026

Experimental Powder X-ray Diffraction Crystal Structure Determination with RealPXRD-Solver

Qi Li, Mingyu Guo, Rui Jiao +14

Determining crystal structures from experimental powder X-ray diffraction data remains challenging because peak overlap, preferred orientation, and impurity phases obscure atomic a…

physics.comp-ph2026

A Graph Neural Network for the Era of Large Atomistic Models

Duo Zhang, Anyang Peng, Chun Cai +11

Foundation models, or large atomistic models (LAMs), aim to universally represent the ground-state potential energy surface (PES) of atomistic systems as defined by density functio…

physics.comp-ph2026

Multi-Task Fine-Tuning Enables Robust Out-of-Distribution Generalization in Atomistic Models

Chengqian Zhang, Duo Zhang, Anyang Peng +7

Accurate de novo molecular and materials design requires structure-property models that generalize beyond known regimes. Although pretrained atomistic models achieve strong in-dist…

physics.comp-ph2025

LAMBench: A Benchmark for Large Atomistic Models

Anyang Peng, Chun Cai, Mingyu Guo +9

Large Atomistic Models (LAMs) have undergone remarkable progress recently, emerging as universal or fundamental representations of the potential energy surface defined by the first…

cs.LG2025

The OpenLAM Challenges

Anyang Peng, Xinzijian Liu, Ming-Yu Guo +2

Inspired by the success of Large Language Models (LLMs), the development of Large Atom Models (LAMs) has gained significant momentum in scientific computation. Since 2022, the Deep…