Stereotyping and Bias in the Flickr30K Dataset
May 19, 2016 ยท Declared Dead ยท ๐ arXiv.org
"No code URL or promise found in abstract"
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Authors
Emiel van Miltenburg
arXiv ID
1605.06083
Category
cs.CL: Computation & Language
Cross-listed
cs.CV
Citations
95
Venue
arXiv.org
Last Checked
4 months ago
Abstract
An untested assumption behind the crowdsourced descriptions of the images in the Flickr30K dataset (Young et al., 2014) is that they "focus only on the information that can be obtained from the image alone" (Hodosh et al., 2013, p. 859). This paper presents some evidence against this assumption, and provides a list of biases and unwarranted inferences that can be found in the Flickr30K dataset. Finally, it considers methods to find examples of these, and discusses how we should deal with stereotype-driven descriptions in future applications.
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