5 papers
EgoMind: Activating Spatial Cognition through Linguistic Reasoning in MLLMs
Zhenghao Chen, Huiqun Wang, Di Huang
Multimodal large language models (MLLMs) are increasingly being applied to spatial cognition tasks, where they are expected to understand and interact with complex environments. Mo…
CoVFT: Context-aware Visual Fine-tuning for Multimodal Large Language Models
Nan Zhou, Huiqun Wang, Yaoyan Zheng +1
Multimodal large language models (MLLMs) achieve remarkable progress in cross-modal perception and reasoning, yet a fundamental question remains unresolved: should the vision encod…
A multimodal vision foundation model for generalizable knee pathology
Kang Yu, Dingyu Wang, Zimu Yuan +8
Musculoskeletal disorders represent a leading cause of global disability, creating an urgent demand for precise interpretation of medical imaging. Current artificial intelligence (…
The Illusion of Clinical Reasoning: A Benchmark Reveals the Pervasive Gap in Vision-Language Models for Clinical Competency
Dingyu Wang, Zimu Yuan, Jiajun Liu +5
Background: The rapid integration of foundation models into clinical practice and public health necessitates a rigorous evaluation of their true clinical reasoning capabilities bey…
Implicit Modeling for Transferability Estimation of Vision Foundation Models
Yaoyan Zheng, Huiqun Wang, Nan Zhou +1
Transferability estimation identifies the best pre-trained models for downstream tasks without incurring the high computational cost of full fine-tuning. This capability facilitate…