1 citations · 1 across the 4 of their papers we have counts for
6 papers
JEPA-Anything: Learning Predictive Models across Different Worlds
Taoyong Cui, Zhongyao Wang, Xinyue Xu +10
World modeling enables intelligence to anticipate consequences, guide interventions, and learn from interaction. Yet predictive models remain domain-specific: can a common learning…
Support Operation Factorization: Compositional Readout of Frozen Vision Encoders under Controlled Interventions
Zhongyao Wang, Wanli Ouyang, Taoyong Cui +1
Compositional analysis of frozen vision encoders should determine both what changed and where it changed. Standard factor probes score these axes separately, however, and can rewar…
Equivariant Evidential Deep Learning for Interatomic Potentials
Zhongyao Wang, Taoyong Cui, Jiawen Zou +5
Uncertainty quantification (UQ) is critical for assessing the reliability of machine learning interatomic potentials (MLIPs) in molecular dynamics (MD) simulations, identifying ext…
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…
Iterative Pretraining Framework for Interatomic Potentials
Taoyong Cui, Zhongyao Wang, Dongzhan Zhou +5
Machine learning interatomic potentials (MLIPs) enable efficient molecular dynamics (MD) simulations with ab initio accuracy and have been applied across various domains in physica…
Policy Learning for Balancing Short-Term and Long-Term Rewards
Peng Wu, Ziyu Shen, Feng Xie +3
Empirical researchers and decision-makers spanning various domains frequently seek profound insights into the long-term impacts of interventions. While the significance of long-ter…