CLEVR-X: A Visual Reasoning Dataset for Natural Language Explanations
Leonard Salewski,
A. Sophia Koepke,
Hendrik P. A. Lensch
et al.
Abstract:Providing explanations in the context of Visual Question Answering (VQA) presents a fundamental problem in machine learning. To obtain detailed insights into the process of generating natural language explanations for VQA, we introduce the large-scale CLEVR-X dataset that extends the CLEVR dataset with natural language explanations. For each image-question pair in the CLEVR dataset, CLEVR-X contains multiple structured textual explanations which are derived from the original scene graphs. By construction, the … Show more
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