9 papers
MicroWorld: Empowering Multimodal Large Language Models to Bridge the Microscopic Domain Gap with Multimodal Attribute Graph
Manyu Li, Ruian He, Chenxi Ma +2
Multimodal large language models (MLLMs) show remarkable potential for scientific reasoning, yet their performance in specialized domains such as microscopy remains limited by the…
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…
Tabular Incremental Inference
Xinda Chen, Zhen Xing, Hanyu Zhang +2
Tabular data is a fundamental form of data structure. The evolution of table analysis tools reflects humanity's continuous progress in data acquisition, management, and processing.…
Non-Uniform Class-Wise Coreset Selection for Vision Model Fine-tuning
Hanyu Zhang, Zhen Xing, Ruian He +4
Coreset selection aims to identify a small yet highly informative subset of data, thereby enabling more efficient model training while reducing storage overhead. Recently, this cap…
MicroVQA++: High-Quality Microscopy Reasoning Dataset with Weakly Supervised Graphs for Multimodal Large Language Model
Manyu Li, Ruian He, Chenxi Ma +2
Multimodal Large Language Models are increasingly applied to biomedical imaging, yet scientific reasoning for microscopy remains limited by the scarcity of large-scale, high-qualit…
Unifying Segment Anything in Microscopy with Vision-Language Knowledge
Manyu Li, Ruian He, Zixian Zhang +3
Accurate segmentation of regions of interest in biomedical images holds substantial value in image analysis. Although several foundation models for biomedical segmentation have cur…