多模态大模型

MDF-MLLM: Deep Fusion Through Cross-Modal Feature Alignment for Contextually Aware Fundoscopic Image Classification

Jason Jordan, Mohammadreza Akbari Lor, Peter Koulen, Mei-Ling Shyu, Shu-Ching Chen

专题命中 多模态训练与对齐 ：MLLM(title,abstract)；cross-modal(title)；multimodal(abstract)；image-text(abstract)

Comments Word count: 5157, Table count: 2, Figure count: 5

On the Value of Cross-Modal Misalignment in Multimodal Representation Learning

Yichao Cai, Yuhang Liu, Erdun Gao, Tianjiao Jiang, Zhen Zhang, Anton van den Hengel, Javen Qinfeng Shi

机构 * Australian Institute for Machine Learning（澳大利亚机器学习研究所） ； The University of Adelaide（阿德莱德大学） 纠错

专题命中 多模态训练与对齐 ：multimodal(title,abstract)；cross-modal(title,abstract)；image-text(abstract)；分类 cs.CV

Comments NeurIPS 2025 camera-ready version (with checklist removed for presentation clarity)

InfiMed-Foundation: Pioneering Advanced Multimodal Medical Models with Compute-Efficient Pre-Training and Multi-Stage Fine-Tuning

Guanghao Zhu, Zhitian Hou, Zeyu Liu, Zhijie Sang, Congkai Xie, Hongxia Yang

机构 * The Hong Kong Polytechnic University（香港理工大学） ； Sun Yat-sen University（中山大学） 纠错

专题命中 多模态训练与对齐 ：multimodal(title,abstract)；分类 cs.CL、cs.AI

Perception-Consistency Multimodal Large Language Models Reasoning via Caption-Regularized Policy Optimization

Songjun Tu, Qichao Zhang, Jingbo Sun, Yuqian Fu, Linjing Li, Xiangyuan Lan, Dongmei Jiang, Yaowei Wang, Dongbin Zhao

机构 * State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Sciences（多模态人工智能系统国家重点实验室，自动化研究所，中国科学院） ； Pengcheng Laboratory（鹏城实验室） ； School of Artificial Intelligence, University of Chinese Academy of Sciences（中国科学院大学人工智能学院） ； Harbin Institute of Technology (Shenzhen)（哈尔滨工业大学（深圳）） 纠错

专题命中 多模态训练与对齐 ：multimodal(title,abstract)；分类 cs.CV、cs.MM

Comments 12pages, 11 figures

Shadow-FT: Tuning Instruct Model via Training on Paired Base Model

Taiqiang Wu, Runming Yang, Jiayi Li, Pengfei Hu, Yik-Chung Wu, Ngai Wong, Yujiu Yang

机构 * The University of Hong Kong（香港大学） ； Tsinghua University（清华大学） ； Tencent（腾讯） 纠错

专题命中 多模态训练与对齐 ：multimodal(abstract)；分类 cs.CL、cs.AI

Comments 24 pages, 12 tables, 8 figures. Previous name: Shadow-FT: Tuning Instruct via Base

Multi-View Hypercomplex Learning for Breast Cancer Screening

Eleonora Lopez, Eleonora Grassucci, Danilo Comminiello

机构 * Department of Information Engineering, Electronics and Telecommunications (DIET), Sapienza University of Rome（信息工程、电子与电信系（DIET），罗马萨皮恩扎大学） 纠错

专题命中 多模态训练与对齐 ：multimodal(abstract)；分类 cs.CV、cs.AI

Comments This paper has been submitted to Expert Systems with Applications

Position IDs Matter: An Enhanced Position Layout for Efficient Context Compression in Large Language Models

Runsong Zhao, Xin Liu, Xinyu Liu, Pengcheng Huang, Chunyang Xiao, Tong Xiao, Jingbo Zhu

机构 * NLP Lab, School of Computer Science and Engineering, Northeastern University, Shenyang, China（东北大学计算机科学与工程学院自然语言处理实验室） ； NiuTrans Research, Shenyang, China（NiuTrans研究院） 纠错

专题命中 多模态训练与对齐 ：multimodal(abstract)；分类 cs.CL

Actions as Language: Fine-Tuning VLMs into VLAs Without Catastrophic Forgetting

Asher J. Hancock, Xindi Wu, Lihan Zha, Olga Russakovsky, Anirudha Majumdar

机构 * Princeton University（普林斯顿大学） 纠错

专题命中 多模态训练与对齐 ：multimodal(abstract)