Knowledge generation for zero-shot knowledge-based VQA

• Main Authors: CAO, Rui, JIANG, Jing
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2024
• Subjects: Artificial Intelligence and Robotics; Numerical Analysis and Scientific Computing
• Online Access: https://ink.library.smu.edu.sg/sis_research/8726; https://ink.library.smu.edu.sg/context/sis_research/article/9729/viewcontent/2024.findings_eacl.36_pvoa.pdf
• Institution: Singapore Management University

Previous solutions to knowledge-based visual question answering (K-VQA) retrieve knowledge from external knowledge bases and use supervised learning to train the K-VQA model. Recently pre-trained LLMs have been used as both a knowledge source and a zero-shot QA model for K-VQA and demonstrated promi...