5 papers
Agentic Fusion of Large Atomic and Language Models to Accelerate Superconductor Discovery
Mingze Li, Yu Rong, Songyou Li +16
Artificial intelligence has accelerated materials discovery through high-throughput prediction and generation, yet the decision problem remains a formidable bottleneck. While curre…
DMFlow: Disordered Materials Generation by Flow Matching
Liming Wu, Rui Jiao, Qi Li +4
The design of materials with tailored properties is crucial for technological progress. However, most deep generative models focus exclusively on perfectly ordered crystals, neglec…
From Macro to Micro: Benchmarking Microscopic Spatial Intelligence on Molecules via Vision-Language Models
Zongzhao Li, Xiangzhe Kong, Jiahui Su +8
This paper introduces the concept of Microscopic Spatial Intelligence (MiSI), the capability to perceive and reason about the spatial relationships of invisible microscopic entitie…
Geometric Mixture Models for Electrolyte Conductivity Prediction
Anyi Li, Jiacheng Cen, Songyou Li +3
Accurate prediction of ionic conductivity in electrolyte systems is crucial for advancing numerous scientific and technological applications. While significant progress has been ma…
STAR-R1: Spatial TrAnsformation Reasoning by Reinforcing Multimodal LLMs
Zongzhao Li, Zongyang Ma, Mingze Li +6
Multimodal Large Language Models (MLLMs) have demonstrated remarkable capabilities across diverse tasks, yet they lag significantly behind humans in spatial reasoning. We investiga…