视觉大模型 / VLM

AMANDA: Agentic Medical Knowledge Augmentation for Data-Efficient Medical Visual Question Answering

Ziqing Wang, Chengsheng Mao, Xiaole Wen, Yuan Luo, Kaize Ding

机构 * Northwestern University（西北大学） ； Microsoft（微软公司） 纠错

专题命中 视觉问答 ：visual question answering(title,abstract)；multimodal large language model(abstract)；分类 cs.AI

Comments EMNLP Findings

LEAML: Label-Efficient Adaptation to Out-of-Distribution Visual Tasks for Multimodal Large Language Models

Ci-Siang Lin, Min-Hung Chen, Yu-Yang Sheng, Yu-Chiang Frank Wang

机构 * Graduate Institute of Communication Engineering, National Taiwan University, Taiwan（台湾国立台湾大学通信工程研究所） ； NVIDIA 纠错

专题命中 视觉问答 ：multimodal large language model(title,abstract)；分类 cs.CV

Q-FSRU: Quantum-Augmented Frequency-Spectral For Medical Visual Question Answering

Rakesh Thakur, Yusra Tariq, Rakesh Chandra Joshi

机构 * Amity University（阿米蒂大学） 纠错

专题命中 视觉问答 ：visual question answering(title,abstract)；分类 cs.CV

Comments 12 pages (9 main + 2 references/appendix), 2 figures, conference paper submitted to ICLR 2026

Ranked from Within: Ranking Large Multimodal Models Without Labels

Weijie Tu, Weijian Deng, Dylan Campbell, Yu Yao, Jiyang Zheng, Tom Gedeon, Tongliang Liu

机构 * Australian National University ； Sydney AI Centre, The University of Sydney ； Curtin University ； University of \'OBuda 纠错

专题命中 视觉问答 ：LLaVA(abstract)；visual question answering(abstract)；分类 cs.CV

Comments ICML 2025 Camera Ready

Exploring OCR-augmented Generation for Bilingual VQA

JoonHo Lee, Sunho Park

机构 * KL-Net, South Korea（韩国KL-Net） 纠错

专题命中 视觉问答 ：vision language model(abstract)；分类 cs.CV

MHier-RAG: Multi-Modal RAG for Visual-Rich Document Question-Answering via Hierarchical and Multi-Granularity Reasoning

Ziyu Gong, Chengcheng Mai, Yihua Huang

专题命中 视觉问答 ：vision-language model(abstract)

Comments Comments: Update Title, Author, Abstract, etc