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VQA task examples.

, 2023
Visual Question Answering (VQA) is a multimodal task that uses natural language to ask and answer questions based on image content. For multimodal tasks, obtaining accurate modality feature information is crucial.
Yangshuyi Xu (16462504), Xiang Shen (127119), Lin Zhang (8926)   +2 more
core   +1 more source

The System of Visual Question Answering: Based on The Architectural Perspective [PDF]

ITM Web of Conferences
With the rapid development of computer vision and natural language processing technology, Visual Question Answering (VQA), as a cross-modal task, has gradually become a research hotspot in the field of artificial intelligence.
Wan Kuangming
doaj   +1 more source

Vision–Language Model for Visual Question Answering in Medical Imagery

Bioengineering, 2023
In the clinical and healthcare domains, medical images play a critical role. A mature medical visual question answering system (VQA) can improve diagnosis by answering clinical questions presented with a medical image.
Yakoub Bazi, Mohamad Mahmoud Al Rahhal, Laila Bashmal, Mansour Zuair   +3 more
doaj   +1 more source

Toward Autonomous Clinics: Human–Robot Collaboration in Clinical Care

MedComm, Volume 7, Issue 8, August 2026.
This graphical abstract summarizes the conceptual structure of human–robot collaboration (HRC) for autonomous clinical systems. The framework is organized around a dual‐brain architecture in which a professional brain supports clinical reasoning tasks such as diagnosis, image analysis, treatment planning, and patient monitoring, while a physical brain ...
Xinyuan Wu, Jingrao Zhang, Mengdi Xu, Henry K. Chu, Xiaolan Chen, Pingting Zhong, Bowen Liu, Mingguang He, Danli Shi   +8 more
wiley   +1 more source

BPI-MVQA: a bi-branch model for medical visual question answering

BMC Medical Imaging, 2022
Background Visual question answering in medical domain (VQA-Med) exhibits great potential for enhancing confidence in diagnosing diseases and helping patients better understand their medical conditions.
Shengyan Liu, Xuejie Zhang, Xiaobing Zhou, Jian Yang   +3 more
doaj   +1 more source

BMPCQA: Bioinspired Metaverse Point Cloud Quality Assessment Based on Large Multimodal Models

Advanced Intelligent Systems, Volume 8, Issue 7, July 2026.
This study presents a bioinspired metaverse point cloud quality assessment metric, which simulates the human visual evaluation process to perform the point cloud quality assessment task. It first extracts rendering projection video features, normal image features, and point cloud patch features, which are then fed into a large multimodal model to ...
Huiyu Duan, Kang Fu, Sijing Wu, Yunhao Li, Zicheng Zhang, Qiang Hu, Xiongkuo Min, Guangtao Zhai   +7 more
wiley   +1 more source

MRAN-VQA: Multimodal Recursive Attention Network for Visual Question Answering

Engineering Science and Technology, an International Journal
Visual Question Answering (VQA) is a fundamental challenge in multimodal AI, requiring models to integrate and reason over both visual and textual information. Despite advancements in deep learning, existing VQA models struggle with multi-step reasoning,
Mohammad Shariful Islam, Mohammad Abu Tareq Rony, Md Murad Hossain Sarker, Md. Khairul Bashar Bhuiyan, Md Saib, Md. Aktarujjaman, Md Shahab Uddin, Abeer D. Algarni, Ahmad Taher Azar, Walid El-Shafai   +9 more
doaj   +1 more source

VQA-MHUG

We present VQA-MHUG - a novel 49-participant dataset of multimodal human gaze on both images and questions during visual question answering (VQA), collected using a high-speed eye tracker.
Kögel, Fabian, Bulling, Andreas, Sood, Ekta   +2 more
core   +1 more source

Generative Artificial Intelligence and Large Language Models in Clinical Oncology

MedComm, Volume 7, Issue 7, July 2026.
By integrating multimodal data, including medical imaging, pathology, omics, and electronic health records, generative AI and LLMs support cancer diagnosis, treatment planning, and follow‐up management. These technologies also enhance physician–patient communication, improve personalized treatment strategies, and leverage intelligent agent automation ...
Yunfang Yu, Zhenhui Zhao, Zehua Wang, Ruichong Lin, Yujie Tan, Yongjian Chen, Ting Li, Daniel Baptista‐Hon, Xiaoxi Zhang, Chuan Wu, Man Tong, Lijun Zheng, Junyan Wu, Olivia Monteiro, Kang Zhang   +14 more
wiley   +1 more source

Zero-Shot Transfer VQA Dataset

CoRR, 2018
Acquiring a large vocabulary is an important aspect of human intelligence. Onecommon approach for human to populating vocabulary is to learn words duringreading or listening, and then use them in writing or speaking. This ability totransfer from input to output is natural for human, but it is difficult for machines.Human spontaneously performs this ...
Yuanpeng Li 0001, Yi Yang 0007, Jianyu Wang, Wei Xu 0017   +3 more
openaire   +2 more sources