59 citations · 262 across the 14 of their papers we have counts for
3 papers · 1 filter
Toward Greater Autonomy in Materials Discovery Agents: Unifying Planning, Physics, and Scientists
Lianhao Zhou, Hongyi Ling, Keqiang Yan +5
We aim at designing language agents with greater autonomy for crystal materials discovery. While most of existing studies restrict the agents to perform specific tasks within prede…
A Materials Foundation Model via Hybrid Invariant-Equivariant Architectures
Keqiang Yan, Montgomery Bohde, Andrii Kryvenko +10
Machine learning interatomic potentials (MLIPs) can predict energy, force, and stress of materials and enable a wide range of downstream discovery tasks. A key design choice in MLI…
Invariant Tokenization of Crystalline Materials for Language Model Enabled Generation
Keqiang Yan, Xiner Li, Hongyi Ling +8
We consider the problem of crystal materials generation using language models (LMs). A key step is to convert 3D crystal structures into 1D sequences to be processed by LMs. Prior…