9 papers
Anatomy-R1: Enhancing Anatomy Reasoning in Multimodal Large Language Models via Anatomical Similarity Curriculum and Group Diversity Augmentation
Ziyang Song, Zelin Zang, Zuyao Chen +6
Multimodal Large Language Models (MLLMs) have achieved impressive progress in natural image reasoning, yet their potential in medical imaging remains underexplored, especially in c…
NeuroABench: A Multimodal Evaluation Benchmark for Neurosurgical Anatomy Identification
Ziyang Song, Zelin Zang, Xiaofan Ye +7
Multimodal Large Language Models (MLLMs) have shown significant potential in surgical video understanding. With improved zero-shot performance and more effective human-machine inte…
Learning Cell-Aware Hierarchical Multi-Modal Representations for Robust Molecular Modeling
Mengran Li, Zelin Zang, Wenbin Xing +4
Understanding how chemical perturbations propagate through biological systems is essential for robust molecular property prediction. While most existing methods focus on chemical s…
Bayesian Test-time Adaptation for Object Recognition and Detection with Vision-language Models
Lihua Zhou, Mao Ye, Shuaifeng Li +7
Vision-language models (VLMs) such as CLIP and Grounding DINO have achieved remarkable success in object recognition and detection. However, their performance often degrades under…
A Fully Open and Generalizable Foundation Model for Ultrasound Clinical Applications
Hongyuan Zhang, Yuheng Wu, Mingyang Zhao +22
Artificial intelligence (AI) that can effectively learn ultrasound representations by integrating multi-source data holds significant promise for advancing clinical care. However,…
SurgLLM: A Versatile Large Multimodal Model with Spatial Focus and Temporal Awareness for Surgical Video Understanding
Zhen Chen, Xingjian Luo, Kun Yuan +6
Surgical video understanding is crucial for facilitating Computer-Assisted Surgery (CAS) systems. Despite significant progress in existing studies, two major limitations persist, i…