e-SNLI-VE is a large VL (vision-language) dataset with NLEs (natural language explanations) with over 430k instances for which the explanations rely on the image content. It has been built by merging the explanations from e-SNLI and the image-sentence pairs from SNLI-VE.
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e-ViL is a benchmark for explainable vision-language tasks. e-ViL spans across three datasets of human-written NLEs (natural language explanations), and provides a unified evaluation framework that is designed to be re-usable for future works.
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The ExBAN dataset: a corpus of NL explanations generated by crowd-sourced participants presented with the task of explaining simple Bayesian Network (BN) graphical representations. These explanations, in a separate collection effort, are rated for clarity and informativeness.
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