ZVQAF: Zero-shot visual question answering with feedback from large language models

Cheng Liu; Chao Wang; Yan Peng; Zhixu Li

doi:10.1016/j.neucom.2024.127505

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ZVQAF: Zero-shot visual question answering with feedback from large language models

Cheng Liu Chao Wang Yan Peng Zhixu Li

Year: 2024 Journal: Neurocomputing Vol: 580 Pages: 127505-127505 Publisher: Elsevier BV

DOI: 10.1016/j.neucom.2024.127505

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Keywords:

Zero (linguistics) Question answering Shot (pellet) Computer science Artificial intelligence Zero-knowledge proof Natural language processing Algorithm Linguistics

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Multimodal Machine Learning Applications

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Domain Adaptation and Few-Shot Learning

Physical Sciences → Computer Science → Artificial Intelligence

Human Pose and Action Recognition

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

ZVQAF: Zero-shot visual question answering with feedback from large language models

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