425 citations · 559 across the 29 of their papers we have counts for
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cs.CV2021★ 1 cited
Are VQA Systems RAD? Measuring Robustness to Augmented Data with Focused Interventions
Daniel Rosenberg, Itai Gat, Amir Feder +1
Deep learning algorithms have shown promising results in visual question answering (VQA) tasks, but a more careful look reveals that they often do not understand the rich signal th…
cs.CV2020★ 21 cited
Removing Bias in Multi-modal Classifiers: Regularization by Maximizing Functional Entropies
Itai Gat, Idan Schwartz, Alexander Schwing +1
Many recent datasets contain a variety of different data modalities, for instance, image, question, and answer data in visual question answering (VQA). When training deep net class…