多模态大模型

Multimodal Carotid Risk Stratification with Large Vision-Language Models: Benchmarking, Fine-Tuning, and Clinical Insights

Daphne Tsolissou, Theofanis Ganitidis, Konstantinos Mitsis, Stergios CHristodoulidis, Maria Vakalopoulou, Konstantina Nikita

机构 * National Technical University of Athens（希腊国家技术大学） ； CentraleSupélec, Université Paris-Saclay（巴黎-萨克雷大学中央理工学院） 纠错

专题命中 图文多模态 ：multimodal(title,abstract)；分类 cs.CV、cs.AI

Med-K2N: Flexible K-to-N Modality Translation for Medical Image Synthesis

Feng Yuan, Yifan Gao, Yuehua Ye, Haoyue Li, Xin Gao

机构 * University of Science and Technology of China（中国科学技术大学） ； Suzhou Institute of Biomedical Engineering and Technology（苏州生物医学工程与技术研究所） ； Chinese Academy of Sciences（中国科学院） ； The Third Affiliated Hospital of Sun Yat-sen University（中山大学第三附属医院） 纠错

专题命中 图文多模态 ：multi-modal(abstract)；cross-modal(abstract)；分类 cs.CV

Comments ICLR2026 under review

Reasoning Riddles: How Explainability Reveals Cognitive Limits in Vision-Language Models

Prahitha Movva

机构 * University of Massachusetts Amherst（马萨诸塞大学阿默斯特分校） 纠错

专题命中 图文多模态 ：multimodal(abstract)；分类 cs.CV

Journal ref COLM 2025: First Workshop on the Application of LLM Explainability to Reasoning and Planning

Same Task, Different Circuits: Disentangling Modality-Specific Mechanisms in VLMs

Yaniv Nikankin, Dana Arad, Yossi Gandelsman, Yonatan Belinkov

机构 * Technion – Israel Institute of Technology（技术学院 – 以色列理工学院） ； UC Berkeley（加州大学伯克利分校） 纠错

专题命中 图文多模态 ：multi-modal(abstract)；分类 cs.CL

Vehicle-Scene Interaction: A Text-Driven 3D Lidar Place Recognition Method for Autonomous Driving

Tianyi Shang, Zhenyu Li, Pengjie Xu, Zhaojun Deng

专题命中 图文多模态 ：cross-modal(abstract)；分类 cs.CV

Comments 13 pages

Toward a Holistic Evaluation of Robustness in CLIP Models

Weijie Tu, Weijian Deng, Tom Gedeon

专题命中 图文多模态 ：multimodal(abstract)；分类 cs.CV

Comments Accepted to IEEE TPAMI, extension of NeurIPS'23 work: A Closer Look at the Robustness of Contrastive Language-Image Pre-Training (CLIP)