28 papers
Active rejection enables reliable generalization of universal machine-learning interatomic potentials
Mingxiang Luo, Xinnan Mao, Lu Wang +3
Universal machine learning interatomic potentials (uMLIPs) bridge quantum-mechanical accuracy and large-scale molecular dynamics, but the cost of high-accuracy calculations such as…
VASP Agent: An Agentic Framework for Autonomous First-principles Calculations
Zeyu Xia, Jinzhe Ma, Congjie Zheng +11
Large Language Models (LLMs) are increasingly embedded in agentic frameworks for scientific discovery. First-principles materials computation imposes a demanding standard for auton…
StraTA: Incentivizing Agentic Reinforcement Learning with Strategic Trajectory Abstraction
Xiangyuan Xue, Yifan Zhou, Zidong Wang +5
Large language models (LLMs) are increasingly used as interactive agents, but optimizing them for long-horizon decision making remains difficult because current methods are largely…
Earth-o1: A Grid-free Observation-native Atmospheric World Model
Junchao Gong, Kaiyi Xu, Wangxu Wei +22
Despite the unprecedented volume of multimodal data provided by modern Earth observation systems, our ability to model atmospheric dynamics remains constrained. Traditional modelin…
An SO(3)-equivariant reciprocal-space neural potential for long-range interactions
Lingfeng Zhang, Taoyong Cui, Dongzhan Zhou +6
Long-range electrostatic and polarization interactions play a central role in molecular and condensed-phase systems, yet remain fundamentally incompatible with locality-based machi…
PhysUniBench: A Multi-Modal Physics Reasoning Benchmark at Undergraduate Level
Lintao Wang, Encheng Su, Jiaqi Liu +11
Physics problem-solving is a challenging domain for AI models, requiring integration of conceptual understanding, mathematical reasoning, and interpretation of physical diagrams. E…