多模态大模型

Towards Cross-modal Backward-compatible Representation Learning for Vision-Language Models

Young Kyun Jang, Ser-nam Lim

机构 * Google DeepMind（谷歌DeepMind） ； University of Central Florida（中央佛罗里达大学） 纠错

专题命中 图文多模态 ：cross-modal(title,abstract)；image-text(abstract)；分类 cs.CV、cs.AI

Mitigating Modal Imbalance in Multimodal Reasoning

Chen Henry Wu, Neil Kale, Aditi Raghunathan

专题命中 图文多模态 ：multimodal(title,abstract)；cross-modal(abstract)；分类 cs.AI

Comments 10 pages, 10 figures, CoLM 2025

Automating construction safety inspections using a multi-modal vision-language RAG framework

Chenxin Wang, Elyas Asadi Shamsabadi, Zhaohui Chen, Luming Shen, Alireza Ahmadian Fard Fini, Daniel Dias-da-Costa

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

Comments 33 pages, 11 figures, 7 tables

Multimodal Arabic Captioning with Interpretable Visual Concept Integration

Passant Elchafei, Amany Fashwan

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

SAR-TEXT: A Large-Scale SAR Image-Text Dataset Built with SAR-Narrator and A Progressive Learning Strategy for Downstream Tasks

Yiguo He, Xinjun Cheng, Junjie Zhu, Chunping Qiu, Jun Wang, Xichuan Zhang, Qiangjuan Huang, Ke Yang

机构 * Intelligent Game and Decision Lab（智能游戏与决策实验室） 纠错

专题命中 图文多模态 ：image-text(title,abstract)；分类 cs.CV

Comments IEEE Submission

SIA: Enhancing Safety via Intent Awareness for Vision-Language Models

Youngjin Na, Sangheon Jeong, Youngwan Lee, Jian Lee, Dawoon Jeong, Youngman Kim

机构 * VLM Safety LAB, MODULABS（视觉语言模型安全实验室，MODULABS） ； ETRI（电子技术研究院） ； KAIST（韩国科学技术院） 纠错

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

Comments Accepted to Safe and Trustworthy Multimodal AI Systems(SafeMM-AI) Workshop at ICCV2025, Non-archival track

Praxis-VLM: Vision-Grounded Decision Making via Text-Driven Reinforcement Learning

Zhe Hu, Jing Li, Zhongzhu Pu, Hou Pong Chan, Yu Yin

机构 * The Hong Kong Polytechnic University（香港理工大学） ； Tsinghua University（清华大学） ； InspireOmni AI ； Alibaba Group（阿里巴巴集团） ； Case Western Reserve University（凯斯西储大学） 纠错

专题命中 图文多模态 ：multimodal(abstract)；image-text(abstract)；分类 cs.CV、cs.CL

Comments Accepted at NeurIPS 2025

MMLongBench: Benchmarking Long-Context Vision-Language Models Effectively and Thoroughly

Zhaowei Wang, Wenhao Yu, Xiyu Ren, Jipeng Zhang, Yu Zhao, Rohit Saxena, Liang Cheng, Ginny Wong, Simon See, Pasquale Minervini, Yangqiu Song, Mark Steedman

机构 * CSE Department, HKUST（香港科技大学计算机科学与工程系） ； Tencent AI Seattle Lab（腾讯AI西雅图实验室） ； University of Edinburgh（爱丁堡大学） ； NVIDIA AI Technology Center (NVAITC), NVIDIA, Santa Clara, USA（英伟达圣克拉拉人工智能技术中心） 纠错

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

Comments Accepted as a spotlight at NeurIPS 2025

DuPLUS: Dual-Prompt Vision-Language Framework for Universal Medical Image Segmentation and Prognosis

Numan Saeed, Tausifa Jan Saleem, Fadillah Maani, Muhammad Ridzuan, Hu Wang, Mohammad Yaqub

机构 * Department of Computer Vision, Mohamed bin Zayed University of Artificial Intelligence (MBZUAI)（计算机视觉系，Mohamed bin Zayed人工智能大学） 纠错

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

Spatial-ViLT: Enhancing Visual Spatial Reasoning through Multi-Task Learning

Chashi Mahiul Islam, Oteo Mamo, Samuel Jacob Chacko, Xiuwen Liu, Weikuan Yu

机构 * Florida State University（佛罗里达州立大学） 纠错

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

Comments 12 pages, 5 figures

A Tale of Two Experts: Cooperative Learning for Source-Free Unsupervised Domain Adaptation

Jiaping Yu, Muli Yang, Jiapeng Ji, Jiexi Yan, Cheng Deng

机构 * School of Electronic Engineering（电子工程学院） ； Xidian University（西安电子科技大学） ； School of Computer Science（计算机科学学院） 纠错

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

Cross-View Open-Vocabulary Object Detection in Aerial Imagery

Jyoti Kini, Rohit Gupta, Mubarak Shah

机构 * Center for Research in Computer Vision, University of Central Florida（计算机视觉研究中心，中央佛罗里达大学） 纠错

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

Probabilistic Language-Image Pre-Training

Sanghyuk Chun, Wonjae Kim, Song Park, Sangdoo Yun

机构 * NAVER AI Lab（NAVER AI实验室） 纠错

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

Comments Code: https://github.com/naver-ai/prolip HuggingFace Hub: https://huggingface.co/collections/SanghyukChun/prolip-6712595dfc87fd8597350291 33 pages, 4.5 MB; LongProLIP paper: arXiv:2503.08048; Multiplicity paper for more background: arxiv.org:2505.19614; v4: fix typos

ViTs: Teaching Machines to See Time Series Anomalies Like Human Experts

Zexin Wang, Changhua Pei, Yang Liu, Hengyue Jiang, Quan Zhou, Haotian Si, Hang Cui, Jianhui Li, Gaogang Xie, Jingjing Li, Dan Pei

机构 * Computer Network Information Center, Chinese Academy of Sciences（中国科学院计算机网络信息中心） ； Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences（中国科学院大学杭州先进研究所） ； Tsinghua University（清华大学） 纠错

专题命中 图文多模态 ：image-text(abstract)

Comments 13 pages