Third International Conference on Computer Science and Communication Technology (ICCSCT 2022) 2022
DOI: 10.1117/12.2661996
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Alleviating shortcut learning behavior of VQA model with context augmentation and adaptive loss adjustment

Abstract: Despite the impressive improvements of Visual Question Answer (VQA), it still remains a challenge of how to avoid the suffering of spurious correlations from textual content to answer. Previous researches have shown that due to the existence of language bias in the VQA dataset, VQA models may tend to capture superficial statistical correlation and suffer from the poor generalization capability in the out-of-distribution data. To alleviate the biases caused by language modality, we propose a method of context a… Show more

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