2 citations · 2 across the 2 of their papers we have counts for
6 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…
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…
Universally Invariant Learning in Equivariant GNNs
Jiacheng Cen, Anyi Li, Ning Lin +5
Equivariant Graph Neural Networks (GNNs) have demonstrated significant success across various applications. To achieve completeness -- that is, the universal approximation property…
ReasonMed: A 370K Multi-Agent Generated Dataset for Advancing Medical Reasoning
Yu Sun, Xingyu Qian, Weiwen Xu +8
Reasoning-based large language models have excelled in mathematics and programming, yet their potential in knowledge-intensive medical question answering remains underexplored and…
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…
Large Language-Geometry Model: When LLM meets Equivariance
Zongzhao Li, Jiacheng Cen, Bing Su +4
Accurately predicting 3D structures and dynamics of physical systems is crucial in scientific applications. Existing approaches that rely on geometric Graph Neural Networks (GNNs)…