Qualitative results of VQA on CLEVR and GQA.

<div><p>Visual question answering (VQA) as an interdisciplinary task of computer vision and natural language processing, estimating the model’s visual reasoning ability, which requires the integration of image information extraction technology and natural language understanding technolog...

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Bibliographic Details
Main Author:	Yao Cong (2552863) (author)
Other Authors:	Hongwei Mo (749819) (author)
Published:	2025
Subjects:	Sociology Science Policy Biological Sciences not elsewhere classified Information Systems not elsewhere classified potential bias states experimental results showed enhance execution performance vqa method based visual reasoning ability traditional vqa methods model &# 8217 improve parsing accuracy program execution stage varied natural language parsing natural language natural language processing task decomposition process task decomposition decomposes natural language reasoning execution task decomposition program accuracy reasoning executor model outperformed comparative model answering accuracy interdisciplinary task usually parses training costs tdn ), promising approach professional benchmark offering advantages multimodal fusion four datasets conducted validation computer vision accurately decompose
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Qualitative results of VQA on CLEVR and GQA.

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