12 papers
Token-Sparse Medical Multimodal Reasoning via Dual-Stream Reinforcement Learning
Kaitao Chen, Weiqian Zhao, Jiamin Wu +6
Vision-language models (VLMs) combining reinforcement learning (RL) ignite remarkable progress in multimodal reasoning, yet still struggle with medical images, which typically exhi…
Data-Centric Foundation Models in Computational Healthcare: A Survey
Yunkun Zhang, Jin Gao, Zheling Tan +5
The advent of foundation models (FMs) as an emerging suite of AI techniques has struck a wave of opportunities in computational healthcare. The interactive nature of these models,…
LUCID-SAE: Learning Unified Vision-Language Sparse Codes for Interpretable Concept Discovery
Difei Gu, Yunhe Gao, Gerasimos Chatzoudis +6
Sparse autoencoders (SAEs) offer a natural path toward comparable explanations across different representation spaces. However, current SAEs are trained per modality, producing dic…
Language-Enhanced Generative Modeling for Amyloid PET Synthesis from MRI and Blood Biomarkers
Zhengjie Zhang, Xiaoxie Mao, Qihao Guo +5
Background: Alzheimer's disease (AD) diagnosis heavily relies on amyloid-beta positron emission tomography (Abeta-PET), which is limited by high cost and limited accessibility. Thi…
Anatomy-VLM: A Fine-grained Vision-Language Model for Medical Interpretation
Difei Gu, Yunhe Gao, Mu Zhou +1
Accurate disease interpretation from radiology remains challenging due to imaging heterogeneity. Achieving expert-level diagnostic decisions requires integration of subtle image fe…
Think Twice to See More: Iterative Visual Reasoning in Medical VLMs
Kaitao Chen, Shaohao Rui, Yankai Jiang +6
Medical vision-language models (VLMs) excel at image-text understanding but typically rely on a single-pass reasoning that neglects localized visual cues. In clinical practice, how…