Taken together, we conclude that fine-grain attribute understanding can benefit from the integration of visual and textual representations.
our results align with previous multimodal research that evaluates vision and language in coarse-grain tasks such as concept similarity and conclude that multimodal representations outperform the unimodal baselines (Lazaridou et al., 2015;Silberer and Lapata, 2014;Kiela and Bottou, 2014).